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TheiaProk Workflow Series

Quick Facts

Workflow Type Applicable Kingdom Last Known Changes Command-line Compatibility Workflow Level
Genomic Characterization Bacteria PHB v2.3.0 Yes, some optional features incompatible Sample-level

TheiaProk Workflows

The TheiaProk workflows are for the assembly, quality assessment, and characterization of bacterial genomes. There are currently four TheiaProk workflows designed to accommodate different kinds of input data:

  1. Illumina paired-end sequencing (TheiaProk_Illumina_PE)
  2. Illumina single-end sequencing (TheiaProk_Illumina_SE)
  3. ONT sequencing (TheiaProk_ONT)
  4. Genome assemblies (TheiaProk_FASTA)

TheiaProk Workflow Diagram

TheiaProk Workflow Diagram

All input reads are processed through "core tasks" in the TheiaProk Illumina and ONT workflows. These undertake read trimming and assembly appropriate to the input data type. TheiaProk workflows subsequently launch default genome characterization modules for quality assessment, species identification, antimicrobial resistance gene detection, sequence typing, and more. For some taxa identified, "taxa-specific sub-workflows" will be automatically activated, undertaking additional taxa-specific characterization steps. When setting up each workflow, users may choose to use "optional tasks" as additions or alternatives to tasks run in the workflow by default.

Inputs

TheiaProk_Illumina_PE Input Read Data

The TheiaProk_Illumina_PE workflow takes in Illumina paired-end read data. Read file names should end with .fastq or .fq, with the optional addition of .gz. When possible, Theiagen recommends zipping files with gzip before Terra uploads to minimize data upload time.

By default, the workflow anticipates 2 x 150bp reads (i.e. the input reads were generated using a 300-cycle sequencing kit). Modifications to the optional parameter for trim_minlen may be required to accommodate shorter read data, such as the 2 x 75bp reads generated using a 150-cycle sequencing kit.

TheiaProk_Illumina_SE Input Read Data

TheiaProk_Illumina_SE takes in Illumina single-end reads. Read file names should end with .fastq or .fq, with the optional addition of .gz. Theiagen highly recommends zipping files with gzip before uploading to Terra to minimize data upload time & save on storage costs.

By default, the workflow anticipates 1 x 35 bp reads (i.e. the input reads were generated using a 70-cycle sequencing kit). Modifications to the optional parameter for trim_minlen may be required to accommodate longer read data.

TheiaProk_ONT Input Read Data

The TheiaProk_ONT workflow takes in base-called ONT read data. Read file names should end with .fastq or .fq, with the optional addition of .gz. When possible, Theiagen recommends zipping files with gzip before uploading to Terra to minimize data upload time.

The ONT sequencing kit and base-calling approach can produce substantial variability in the amount and quality of read data. Genome assemblies produced by the TheiaProk_ONT workflow must be quality assessed before reporting results.

TheiaProk_FASTA Input Assembly Data

The TheiaProk_FASTA workflow takes in assembly files in FASTA format.

Terra Task name Variable Type Description Default value Terra Status Workflow
*workflow name samplename String Name of sample to be analyzed Required FASTA, ONT, PE, SE
theiaprok_fasta assembly_fasta File Assembly file in fasta format Required FASTA
theiaprok_illumina_pe read1 File Illumina forward read file in FASTQ file format (compression optional) Required PE
theiaprok_illumina_pe read2 File Illumina reverse read file in FASTQ file format (compression optional) Required PE
theiaprok_illumina_se read1 File Illumina forward read file in FASTQ file format (compression optional) Required SE
theiaprok_ont read1 File Base-called ONT read file in FASTQ file format (compression optional) Required ONT
*workflow name abricate_db String Database to use with the Abricate tool. Options: NCBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB vfdb Optional FASTA, ONT, PE, SE
*workflow name call_abricate Boolean Set to true to enable the Abricate task FALSE Optional FASTA, ONT, PE, SE
*workflow name call_ani Boolean Set to true to enable the ANI task FALSE Optional FASTA, ONT, PE, SE
*workflow name call_kmerfinder Boolean Set to true to enable the kmerfinder task FALSE Optional FASTA, ONT, PE, SE
*workflow name call_plasmidfinder Boolean Set to true to enable the plasmidfinder task TRUE Optional FASTA, ONT, PE, SE
*workflow name call_resfinder Boolean Set to true to enable the ResFinder task FALSE Optional FASTA, ONT, PE, SE
*workflow name city String Will be used in the "city" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name collection_date String Will be used in the "collection_date" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name county String Will be used in the "county" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name expected_taxon String If provided, this input will override the taxonomic assignment made by GAMBIT and launch the relevant taxon-specific submodules. It will also modify the organism flag used by AMRFinderPlus. Example format: "Salmonella enterica" Optional FASTA, ONT, PE, SE
*workflow name genome_annotation String If set to "bakta", TheiaProk will use Bakta rather than Prokka to annotate the genome prokka Optional FASTA, ONT, PE, SE
*workflow name genome_length Int User-specified expected genome length to be used in genome statistics calculations Optional ONT, PE, SE
*workflow name max_genome_length Int Maximum genome length able to pass read screening. For TheiaProk_ONT, screening using max_genome_length is skipped by default. 18040666 Optional ONT, PE, SE
*workflow name min_basepairs Int Minimum number of base pairs able to pass read screening 2241820 Optional ONT, PE, SE
*workflow name min_coverage Int Minimum genome coverage able to pass read screening. Screening using min_coverage is skipped by default. 5 Optional ONT
*workflow name min_coverage Int Minimum genome coverage able to pass read screening 10 Optional PE, SE
*workflow name min_genome_length Int Minimum genome length able to pass read screening. For TheiaProk_ONT, screening using min_genome_length is skipped by default. 100000 Optional ONT, PE, SE
*workflow name min_proportion Int Minimum proportion of total reads in each read file to pass read screening 40 Optional PE
*workflow name min_reads Int Minimum number of reads to pass read screening 5000 Optional ONT
*workflow name min_reads Int Minimum number of reads to pass read screening 7472 Optional PE, SE
*workflow name originating_lab String Will be used in the "originating_lab" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name perform_characterization Boolean Set to "false" if you want to only generate an assembly and relevant QC metrics and skip all characterization tasks TRUE Optional FASTA, ONT, PE, SE
*workflow name qc_check_table File TSV value with taxons for rows and QC values for columns; internal cells represent user-determined QC thresholds; if provided, turns on the QC Check task.
Click on the variable name for an example QC Check table		 Optional FASTA, ONT, PE, SE
*workflow name read1_lane2 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name read1_lane3 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name read1_lane4 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name read2_lane2 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name read2_lane3 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name read2_lane4 File If provided, the Concatenate_Illumina_Lanes subworkflow will concatenate all files from the same lane before doing any subsequent analysis Optional PE, SE
*workflow name run_id String Will be used in the "run_id" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name seq_method String Will be used in the "seq_id" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
*workflow name skip_mash Boolean If true, skips estimation of genome size and coverage in read screening steps. As a result, providing true also prevents screening using these parameters. TRUE Optional ONT, SE
*workflow name skip_screen Boolean Option to skip the read screening prior to analysis FALSE Optional ONT, PE, SE
*workflow name taxon_tables File File indicating data table names to copy samples of a particular taxon to Optional FASTA, ONT, PE, SE
*workflow name terra_project String The name of the Terra Project where you want the taxon tables written to Optional FASTA, ONT, PE, SE
*workflow name terra_workspace String The name of the Terra Workspace where you want the taxon tables written to Optional FASTA, ONT, PE, SE
*workflow name trim_min_length Int Specifies minimum length of each read after trimming to be kept 25 Optional SE
*workflow name trim_min_length Int Specifies minimum length of each read after trimming to be kept 75 Optional PE
*workflow name trim_quality_min_score Int Specifies the minimum average quality of bases in a sliding window to be kept 20 Optional PE
*workflow name trim_quality_trim_score Int Specifies the average quality of bases in a sliding window to be kept 30 Optional SE
*workflow name trim_window_size Int Specifies window size for trimming (the number of bases to average the quality across) 4 Optional SE
*workflow name trim_window_size Int Specifies window size for trimming (the number of bases to average the quality across) 4 Optional PE
*workflow name zip String Will be used in the "zip" column in any taxon-specific tables created in the Export Taxon Tables task Optional FASTA, ONT, PE, SE
abricate cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
abricate disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
abricate docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/abricate:1.0.1-abaum-plasmid Optional FASTA, ONT, PE, SE
abricate memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
abricate mincov Int Minimum DNA %coverage for the Abricate task 80 Optional FASTA, ONT, PE, SE
abricate minid Int Minimum DNA %identity for the Abricate task 80 Optional FASTA, ONT, PE, SE
amrfinderplus_task cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
amrfinderplus_task detailed_drug_class Boolean If set to true, amrfinderplus_amr_classes and amrfinderplus_amr_subclasses outputs will be created FALSE Optional FASTA, ONT, PE, SE
amrfinderplus_task disk_size Boolean Amount of storage (in GB) to allocate to the AMRFinderPlus task 50 Optional FASTA, ONT, PE, SE
amrfinderplus_task docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/ncbi-amrfinderplus:3.12.8-2024-07-22.1 Optional FASTA, ONT, PE, SE
amrfinderplus_task hide_point_mutations Boolean If set to true, point mutations are not reported FALSE Optional FASTA, ONT, PE, SE
amrfinderplus_task memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
amrfinderplus_task mincov Float Minimum proportion of reference gene covered for a BLAST-based hit (Methods BLAST or PARTIAL)." Attribute should be a float ranging from 0-1, such as 0.6 (equal to 60% coverage) 0.5 Optional FASTA, ONT, PE, SE
amrfinderplus_task minid Float "Minimum identity for a blast-based hit hit (Methods BLAST or PARTIAL). -1 means use a curated threshold if it exists and 0.9 otherwise. Setting this value to something other than -1 will override any curated similarity cutoffs." Attribute should be a float ranging from 0-1, such as 0.95 (equal to 95% identity) 0.9 Optional FASTA, ONT, PE, SE
amrfinderplus_task separate_betalactam_genes Boolean Report beta-Lactam AMR genes separated out by all beta-lactam and the respective beta-lactam subclasses FALSE Optional FASTA, ONT, PE, SE
ani ani_threshold Float ANI value threshold must be surpassed in order to output the ani_top_species_match. If a genome does not surpass this threshold (and the percent_bases_aligned_threshold) then the ani_top_species_match output String will show a warning instead of a genus & species. 80 Optional FASTA, ONT, PE, SE
ani cpu Int Number of CPUs to allocate to the task 4 Optional FASTA, ONT, PE, SE
ani disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
ani docker String The Docker container to use for the task "us-docker.pkg.dev/general-theiagen/staphb/mummer:4.0.0-rgdv2 Optional FASTA, ONT, PE, SE
ani mash_filter Float Mash distance threshold over which ANI is not calculated 0.9 Optional FASTA, ONT, PE, SE
ani memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
ani percent_bases_aligned_threshold Float Threshold regarding the proportion of bases aligned between the query genome and reference genome. If a genome does not surpass this threshold (and the ani_threshold) then the ani_top_species_match output String will show a warning instead of a genus & species. 70 Optional FASTA, ONT, PE, SE
ani ref_genome File If not set, uses all 43 genomes in RGDv2 Optional FASTA, ONT, PE, SE
bakta bakta_db File Database of reference annotations (seehttps://github.com/oschwengers/bakta#database) gs://theiagen-public-files-rp/terra/theiaprok-files/bakta_db_2022-08-29.tar.gz Optional FASTA, ONT, PE, SE
bakta bakta_opts String Parameters to pass to bakta from https://github.com/oschwengers/bakta#usage Optional FASTA, ONT, PE, SE
bakta compliant Boolean If true, forces Genbank/ENA/DDJB compliance FALSE Optional FASTA, ONT, PE, SE
bakta cpu Int Number of CPUs to allocate to the task 8 Optional FASTA, ONT, PE, SE
bakta disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
bakta docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/bakta:1.5.1--pyhdfd78af_0 Optional FASTA, ONT, PE, SE
bakta memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional FASTA, ONT, PE, SE
bakta prodigal_tf File Prodigal training file to use for CDS prediction by bakta Optional FASTA, ONT, PE, SE
bakta proteins Boolean FALSE Optional FASTA, ONT, PE, SE
busco cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
busco disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
busco docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/ezlabgva/busco:v5.7.1_cv1 Optional FASTA, ONT, PE, SE
busco eukaryote Boolean Assesses eukaryotic organisms, rather than prokaryotic organisms FALSE Optional FASTA, ONT, PE, SE
busco memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
cg_pipeline_clean cg_pipe_opts String Options to pass to CG-Pipeline for clean read assessment --fast Optional PE, SE
cg_pipeline_clean cpu Int Number of CPUs to allocate to the task 4 Optional PE, SE
cg_pipeline_clean disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional PE, SE
cg_pipeline_clean docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/lyveset:1.1.4f Optional PE, SE
cg_pipeline_clean memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional PE, SE
cg_pipeline_clean read2 File Internal component, do not modify Do not modify, Optional SE
cg_pipeline_raw cg_pipe_opts String Options to pass to CG-Pipeline for raw read assessment --fast Optional PE, SE
cg_pipeline_raw cpu Int Number of CPUs to allocate to the task 4 Optional PE, SE
cg_pipeline_raw disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional PE, SE
cg_pipeline_raw docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/lyveset:1.1.4f Optional PE, SE
cg_pipeline_raw memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional PE, SE
cg_pipeline_raw read2 File Internal component, do not modify Do not modify, Optional SE
clean_check_reads cpu Int Number of CPUs to allocate to the task 2 Optional ONT, PE, SE
clean_check_reads disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional ONT, PE, SE
clean_check_reads docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/bactopia/gather_samples:2.0.2 Optional ONT, PE, SE
clean_check_reads memory Int Amount of memory/RAM (in GB) to allocate to the task 2 Optional ONT, PE, SE
clean_check_reads organism String Internal component, do not modify Do not modify, Optional ONT, PE, SE
clean_check_reads workflow_series String Internal component, do not modify Do not modify, Optional ONT, PE, SE
dragonflye assembler String The assembler to use in dragonflye. Three options: raven, miniasm, flye flye Optional ONT
dragonflye assembler_options String Enables extra assembler options in quote Optional ONT
dragonflye cpu Int Number of CPUs to allocate to the task 4 Optional ONT
dragonflye disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional ONT
dragonflye docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/dragonflye:1.0.14--hdfd78af_0 Optional ONT
dragonflye illumina_polishing_rounds Int Number of polishing rounds to conduct with Illumina data 1 Optional ONT
dragonflye illumina_read1 File If Illumina reads are provided, Dragonflye will perform Illumina polishing Optional ONT
dragonflye illumina_read2 File If Illumina reads are provided, Dragonflye will perform Illumina polishing Optional ONT
dragonflye medaka_model String The model of medaka to use for assembly r941_min_hac_g507 Optional ONT
dragonflye memory Int Amount of memory/RAM (in GB) to allocate to the task 32 Optional ONT
dragonflye polishing_rounds Int The number of polishing rounds to conduct (without Illumina) 1 Optional ONT
dragonflye use_pilon_illumina_polisher Boolean Set to true to use Pilon to polish Illumina reads FALSE Optional ONT
dragonflye use_racon Boolean Set to true to use Racon to polish instead of Medaka FALSE Optional ONT
export_taxon_tables asembly_fasta File Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables bbduk_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT
export_taxon_tables cg_pipeline_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT
export_taxon_tables cg_pipeline_report_clean File Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables cg_pipeline_report_raw File Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables combined_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables combined_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables combined_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables combined_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables contigs_gfa File Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables cpu Int Number of CPUs to allocate to the task 1 Optional FASTA, ONT, PE, SE
export_taxon_tables disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
export_taxon_tables docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/theiagen/terra-tools:2023-03-16 Optional FASTA, ONT, PE, SE
export_taxon_tables dragonflye_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables emmtypingtool_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT, SE
export_taxon_tables emmtypingtool_emm_type String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables emmtypingtool_results_xml File Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables emmtypingtool_version String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables est_coverage_clean Float Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables est_coverage_raw Float Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables fastp_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables fastq_scan_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables hicap_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT
export_taxon_tables hicap_genes String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables hicap_results_tsv File Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables hicap_serotype String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables hicap_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables kmc_est_genome_length String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables kmc_kmer_stats File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables kmc_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables kraken2_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT, PE
export_taxon_tables kraken2_report String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables kraken2_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
export_taxon_tables midas_docker String The Docker container to use for the task Do not modify, Optional FASTA, ONT
export_taxon_tables midas_primary_genus String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables midas_report File Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables midas_secondary_genus String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables midas_secondary_genus_abundance Float Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables midas_secondary_genus_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables nanoplot_docker String The Docker container to use for the task Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_html_clean File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_html_raw File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_num_reads_clean1 Int Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_num_reads_raw1 Int Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_est_coverage_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_est_coverage_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_median_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_median_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_median_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_median_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_n50_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_n50_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_stdev_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_r1_stdev_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_tsv_clean File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_tsv_raw File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoplot_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables nanoq_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables num_reads_clean_pairs String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables num_reads_clean1 Int Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables num_reads_clean2 Int Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables num_reads_raw_pairs String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables num_reads_raw1 Int Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables num_reads_raw2 Int Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables r1_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE
export_taxon_tables r1_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables r1_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE
export_taxon_tables r1_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables r2_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables r2_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables rasusa_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables read1 File Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables read1_clean File Internal component, do not modify Do not modify, Optional FASTA
export_taxon_tables read2 File Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables read2_clean File Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables seroba_ariba_identity String Internal component, do not modify Do not modify, Optional ONT, SE
export_taxon_tables seroba_ariba_serotype String Internal component, do not modify Do not modify, Optional ONT, SE
export_taxon_tables seroba_details File Internal component, do not modify Do not modify, Optional ONT, SE
export_taxon_tables seroba_docker String The Docker container to use for the task Do not modify, Optional ONT, SE
export_taxon_tables seroba_serotype String Internal component, do not modify Do not modify, Optional ONT, SE
export_taxon_tables seroba_version String Internal component, do not modify Do not modify, Optional ONT, SE
export_taxon_tables shigeifinder_cluster_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_docker_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_H_antigen_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_ipaH_presence_absence_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_notes_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_num_virulence_plasmid_genes String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_O_antigen_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_report_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_serotype_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shigeifinder_version_reads String Internal component, do not modify Do not modify, Optional ONT
export_taxon_tables shovill_pe_version String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables shovill_se_version String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE
export_taxon_tables srst2_vibrio_biotype String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_ctxA String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_detailed_tsv String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_ompW String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_serogroup String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_toxR String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables srst2_vibrio_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
export_taxon_tables theiaprok_fasta_analysis_date String Internal component, do not modify Do not modify, Optional ONT, PE, SE
export_taxon_tables theiaprok_fasta_version String Internal component, do not modify Do not modify, Optional ONT, PE, SE
export_taxon_tables theiaprok_illumina_pe_analysis_date String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables theiaprok_illumina_pe_version String Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
export_taxon_tables theiaprok_illumina_se_analysis_date String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE
export_taxon_tables theiaprok_illumina_se_version String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE
export_taxon_tables theiaprok_ont_analysis_date String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables theiaprok_ont_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables tiptoft_plasmid_replicon_fastq File Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables tiptoft_plasmid_replicon_genes String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables tiptoft_version String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
export_taxon_tables trimmomatic_version String Internal component, do not modify Do not modify, Optional FASTA, ONT
gambit cpu Int Number of CPUs to allocate to the task 8 Optional FASTA, ONT, PE, SE
gambit disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
gambit docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/gambit:1.0.0 Optional FASTA, ONT, PE, SE
gambit gambit_db_genomes File User-provided database of assembled query genomes; requires complementary signatures file. If not provided, uses default database, "/gambit-db" gs://gambit-databases-rp/2.0.0/gambit-metadata-2.0.0-20240628.gdb Optional FASTA, ONT, PE, SE
gambit gambit_db_signatures File User-provided signatures file; requires complementary genomes file. If not specified, the file from the docker container will be used. gs://gambit-databases-rp/2.0.0/gambit-signatures-2.0.0-20240628.gs Optional FASTA, ONT, PE, SE
gambit memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional FASTA, ONT, PE, SE
kmerfinder cpu Int Number of CPUs to allocate to the task 4 Optional FASTA, ONT, PE, SE
kmerfinder disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
kmerfinder docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/kmerfinder:3.0.2--hdfd78af_0 Optional FASTA, ONT, PE, SE
kmerfinder kmerfinder_args String Kmerfinder additional arguments Optional FASTA, ONT, PE, SE
kmerfinder kmerfinder_db String Bacterial database for KmerFinder gs://theiagen-public-files-rp/terra/theiaprok-files/kmerfinder_bacteria_20230911.tar.gz Optional FASTA, ONT, PE, SE
kmerfinder memory Int Amount of memory/RAM (in GB) to allocate to the task 32 Optional FASTA, ONT, PE, SE
merlin_magic abricate_abaum_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/abricate:1.0.1-abaum-plasmid Optional FASTA, ONT, PE, SE
merlin_magic abricate_abaum_mincov Int Minimum DNA percent coverage Optional FASTA, ONT, PE, SE
merlin_magic abricate_abaum_minid Int Minimum DNA percent identity; set to 95 because there is a strict threshold of 95% identity for typing purposes 95 Optional FASTA, ONT, PE, SE
merlin_magic abricate_vibrio_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/abricate:1.0.1-abaum-plasmid Optional FASTA, ONT, PE, SE
merlin_magic abricate_vibrio_mincov Int Minimum DNA percent coverage 80 Optional FASTA, ONT, PE, SE
merlin_magic abricate_vibrio_minid Int Minimum DNA percent identity 80 Optional FASTA, ONT, PE, SE
merlin_magic agrvate_agr_typing_only Boolean Set to true to skip agr operon extraction and frameshift detection False Optional FASTA, ONT, PE, SE
merlin_magic agrvate_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/agrvate:1.0.2--hdfd78af_0 Optional FASTA, ONT, PE, SE
merlin_magic assembly_only Boolean Internal component, do not modify Do not modify, Optional ONT, PE, SE
merlin_magic call_poppunk Boolean If "true", runs PopPUNK for GPSC cluster designation for S. pneumoniae TRUE Optional FASTA, ONT, PE, SE
merlin_magic call_shigeifinder_reads_input Boolean If set to "true", the ShigEiFinder task will run again but using read files as input instead of the assembly file. Input is shown but not used for TheiaProk_FASTA. FALSE Optional FASTA, ONT, PE, SE
merlin_magic call_stxtyper Boolean If set to "true", the StxTyper task will run on all samples regardless of the gambit_predicted_taxon output. Useful if you suspect a non-E.coli or non-Shigella sample contains stx genes. FALSE Optional FASTA, ONT, PE, SE
merlin_magic call_tbp_parser Boolean If set to "true", activates the tbp_parser module and results in more outputs, including tbp_parser_looker_report_csv, tbp_parser_laboratorian_report_csv, tbp_parser_lims_report_csv, tbp_parser_coverage_report, and tbp_parser_genome_percent_coverage FALSE Optional FASTA, ONT, PE, SE
merlin_magic cauris_cladetyper_docker_image String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_kmer_size Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade1 File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade1_annotated File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade2 File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade2_annotated File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade3 File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade3_annotated File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade4 File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade4_annotated File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade5 File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic cladetyper_ref_clade5_annotated File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic clockwork_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/cdcgov/varpipe_wgs_with_refs:2bc7234074bd53d9e92a1048b0485763cd9bbf6f4d12d5a1cc82bfec8ca7d75e Optional FASTA, ONT, PE, SE
merlin_magic ectyper_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/ectyper:1.0.0--pyhdfd78af_1 Optional FASTA, ONT, PE, SE
merlin_magic ectyper_hpcov Int Minumum percent coverage required for an H antigen allele match 50 Optional FASTA, ONT, PE, SE
merlin_magic ectyper_hpid Int Percent identity required for an H antigen allele match 95 Optional FASTA, ONT, PE, SE
merlin_magic ectyper_opcov Int Minumum percent coverage required for an O antigen allele match 90 Optional FASTA, ONT, PE, SE
merlin_magic ectyper_opid Int Percent identity required for an O antigen allele match 90 Optional FASTA, ONT, PE, SE
merlin_magic ectyper_print_alleles Boolean Set to true to print the allele sequences as the final column False Optional FASTA, ONT, PE, SE
merlin_magic ectyper_verify Boolean Set to true to enable E. coli species verification False Optional FASTA, ONT, PE, SE
merlin_magic emmtypingtool_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/emmtypingtool:0.0.1 Optional FASTA, ONT, PE, SE
merlin_magic genotyphi_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/mykrobe:0.11.0 Optional FASTA, ONT, PE, SE
merlin_magic hicap_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/hicap:1.0.3--py_0 Optional FASTA, ONT, PE, SE
merlin_magic kaptive_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/kaptive:2.0.3 Optional FASTA, ONT, PE, SE
merlin_magic kaptive_low_gene_id Float Percent identity threshold for what counts as a low identity match in the gene BLAST search 95 Optional FASTA, ONT, PE, SE
merlin_magic kaptive_min_coverage Float Minimum required percent identity for the gene BLAST search via tBLASTn 80 Optional FASTA, ONT, PE, SE
merlin_magic kaptive_min_identity Float Minimum required percent coverage for the gene BLAST search via tBLASTn 90 Optional FASTA, ONT, PE, SE
merlin_magic kaptive_start_end_margin Int Determines flexibility in identifying the start and end of a locus - if this value is 10, a locus match that is missing the first 8 base pairs will still count as capturing the start of the locus 10 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/kleborate:2.2.0 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_min_coverage Float Minimum alignment percent coverage for main results 80 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_min_identity Float Minimum alignment percent identity for main results 90 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_min_kaptive_confidence String {None,Low,Good,High,Very_high,Perfect} Minimum Kaptive confidence to call K/O loci - confidence levels below this will be reported as unknown Good Optional FASTA, ONT, PE, SE
merlin_magic kleborate_min_spurious_coverage Float Minimum alignment percent coverage for spurious results 40 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_min_spurious_identity Float Minimum alignment percent identity for spurious results 80 Optional FASTA, ONT, PE, SE
merlin_magic kleborate_skip_kaptive Boolean Equivalent to --kaptive_k --kaptive_ False Optional FASTA, ONT, PE, SE
merlin_magic kleborate_skip_resistance Boolean Set to true to turn on resistance genes screening (default: no resistance gene screening) False Optional FASTA, ONT, PE, SE
merlin_magic legsta_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/legsta:0.5.1--hdfd78af_2 Optional FASTA, ONT, PE, SE
merlin_magic lissero_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/lissero:0.4.9--py_0 Optional FASTA, ONT, PE, SE
merlin_magic lissero_min_cov Float Minimum coverage of the gene to accept a match 95 Optional FASTA, ONT, PE, SE
merlin_magic lissero_min_id Float Minimum percent identity to accept a match 95 Optional FASTA, ONT, PE, SE
merlin_magic meningotype_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/meningotype:0.8.5--pyhdfd78af_0 Optional FASTA, ONT, PE, SE
merlin_magic ngmaster_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/ngmaster:1.0.0 Optional FASTA, ONT, PE, SE
merlin_magic ont_data Boolean Internal component, do not modify Do not modify, Optional FASTA, PE, SE
merlin_magic paired_end Boolean Internal component, do not modify Do not modify, Optional ONT, PE
merlin_magic pasty_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/pasty:1.0.3 Optional FASTA, ONT, PE, SE
merlin_magic pasty_min_coverage Int Minimum coverage of a O-antigen to be considered for serogrouping by pasty 95 Optional FASTA, ONT, PE, SE
merlin_magic pasty_min_pident Int Minimum percent identity for a blast hit to be considered for serogrouping 95 Optional FASTA, ONT, PE, SE
merlin_magic pbptyper_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/pbptyper:1.0.4 Optional FASTA, ONT, PE, SE
merlin_magic pbptyper_min_coverage Int Minimum percent coverage to count a hit 90 Optional FASTA, ONT, PE, SE
merlin_magic pbptyper_min_pident Int Minimum percent identity to count a hit 90 Optional FASTA, ONT, PE, SE
merlin_magic poppunk_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/poppunk:2.4.0 Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_clusters_csv File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_clusters.csv Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_dists_npy File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.dists.npy Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_dists_pkl File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.dists.pkl Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_external_clusters_csv File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_external_clusters.csv Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_fit_npz File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_fit.npz Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_fit_pkl File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_fit.pkl Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_graph_gt File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_graph.gt Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_h5 File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.h5 Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_qcreport_txt File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_qcreport.txt Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_refs File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.refs Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_refs_dists_npy File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.refs.dists.npy Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_refs_dists_pkl File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.refs.dists.pkl Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_refs_graph_gt File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6refs_graph.gt Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_refs_h5 File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6.refs.h5 Optional FASTA, ONT, PE, SE
merlin_magic poppunk_gps_unword_clusters_csv File Poppunk database file *Provide an empty or local file if running TheiaProk on the command-line gs://theiagen-public-files-rp/terra/theiaprok-files/GPS_v6/GPS_v6_unword_clusters.csv Optional FASTA, ONT, PE, SE
merlin_magic read1 File Internal component, do not modify Do not modify, Optional FASTA
merlin_magic read2 File Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
merlin_magic seqsero2_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/seqsero2:1.2.1 Optional FASTA, ONT, PE, SE
merlin_magic seroba_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/seroba:1.0.2 Optional FASTA, ONT, PE, SE
merlin_magic serotypefinder_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/serotypefinder:2.0.1 Optional FASTA, ONT, PE, SE
merlin_magic shigatyper_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/shigatyper:2.0.5 Optional FASTA, ONT, PE, SE
merlin_magic shigeifinder_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/shigeifinder:1.3.5 Optional FASTA, ONT, PE, SE
merlin_magic sistr_cpu Int The number of CPU cores to allocate for the task 8 Optional FASTA, ONT, PE, SE
merlin_magic sistr_disk_size Int The disk size (in GB) to allocate for the task 100 Optional FASTA, ONT, PE, SE
merlin_magic sistr_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/sistr_cmd:1.1.1--pyh864c0ab_2 Optional FASTA, ONT, PE, SE
merlin_magic sistr_memory Int The amount of memory (in GB) to allocate for the task. 32 Optional FASTA, ONT, PE, SE
merlin_magic sistr_use_full_cgmlst_db Boolean Set to true to use the full set of cgMLST alleles which can include highly similar alleles. By default the smaller "centroid" alleles or representative alleles are used for each marker False Optional FASTA, ONT, PE, SE
merlin_magic snippy_base_quality Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_gene_query_docker_image String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_map_qual Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_maxsoft Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_min_coverage Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_min_frac Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_min_quality Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_query_gene String Internal component, do not modify Do not modify, Optional FASTA, PE, SE
merlin_magic snippy_reference_afumigatus File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_reference_calbicans File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_reference_cryptoneo File *Provide an empty file if running TheiaProk on the command-line Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic snippy_variants_docker_image String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic sonneityping_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/mykrobe:0.12.1 Optional FASTA, ONT, PE, SE
merlin_magic sonneityping_mykrobe_opts String Additional options for mykrobe in sonneityping Optional FASTA, ONT, PE, SE
merlin_magic spatyper_do_enrich Boolean Set to true to enable PCR product enrichment False Optional FASTA, ONT, PE, SE
merlin_magic spatyper_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/spatyper:0.3.3--pyhdfd78af_3 Optional FASTA, ONT, PE, SE
merlin_magic srst2_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/srst2:0.2.0-vcholerae Optional FASTA, ONT, PE, SE
merlin_magic srst2_gene_max_mismatch Int Maximum number of mismatches for SRST2 to call a gene as present 2000 Optional FASTA, ONT, PE, SE
merlin_magic srst2_max_divergence Int Maximum divergence, in percentage, for SRST2 to call a gene as present 20 Optional FASTA, ONT, PE, SE
merlin_magic srst2_min_cov Int Minimum breadth of coverage for SRST2 to call a gene as present 80 Optional FASTA, ONT, PE, SE
merlin_magic srst2_min_depth Int Minimum depth of coverage for SRST2 to call a gene as present 5 Optional FASTA, ONT, PE, SE
merlin_magic srst2_min_edge_depth Int Minimum edge depth for SRST2 to call a gene as present 2 Optional FASTA, ONT, PE, SE
merlin_magic stxtyper_cpu Int The number of CPU cores to allocate for the task. 1 Optional FASTA, ONT, PE, SE
merlin_magic stxtyper_disk_size Int Amount of storage (in GB) to allocate to the task 50 Optional FASTA, ONT, PE, SE
merlin_magic stxtyper_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/stxtyper:1.0.24 Optional FASTA, ONT, PE, SE
merlin_magic stxtyper_enable_debug Boolean When enabled, additional messages are printed and files in $TMPDIR are not removed after running FALSE Optional FASTA, ONT, PE, SE
merlin_magic stxtyper_memory Int Amount of memory (in GB) to allocate to the task 4 Optional FASTA, ONT, PE, SE
merlin_magic staphopia_sccmec_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/biocontainers/staphopia-sccmec:1.0.0--hdfd78af_0 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_add_cs_lims Boolean Set to true add cycloserine results to the LIMS report FALSE Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_coverage_regions_bed File A bed file that lists the regions to be considered for QC Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_coverage_threshold Int The minimum coverage for a region to pass QC in tbp_parser 100 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_debug Boolean Activate the debug mode on tbp_parser; increases logging outputs TRUE Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/theiagen/tbp-parser:2.2.2 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_etha237_frequency Float Minimum frequency for a mutation in ethA at protein position 237 to pass QC in tbp-parser 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_expert_rule_regions_bed File A file that contains the regions where R mutations and expert rules are applied Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_min_depth Int Minimum depth for a variant to pass QC in tbp_parser 10 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_min_frequency Int The minimum frequency for a mutation to pass QC 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_min_read_support Int The minimum read support for a mutation to pass QC 10 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_operator String Fills the "operator" field in the tbp_parser output files Operator not provided Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_output_seq_method_type String Fills out the "seq_method" field in the tbp_parser output files Sequencing method not provided Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_rpob449_frequency Float Minimum frequency for a mutation at protein position 449 to pass QC in tbp-parser 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_rrl_frequency Float Minimum frequency for a mutation in rrl to pass QC in tbp-parser 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_rrl_read_support Int Minimum read support for a mutation in rrl to pass QC in tbp-parser 10 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_rrs_frequency Float Minimum frequency for a mutation in rrs to pass QC in tbp-parser 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_rrs_read_support Int Minimum read support for a mutation in rrs to pass QC in tbp-parser 10 Optional FASTA, ONT, PE, SE
merlin_magic tbp_parser_tngs_data Boolean Set to true to enable tNGS-specific parameters and runs in tbp-parser FALSE Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_custom_db File TBProfiler uses by default the TBDB database; if you have a custom database you wish to use, you must provide a custom database in this field and set tbprofiler_run_custom_db to true Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/tbprofiler:4.4.2 Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_mapper String The mapping tool used in TBProfiler to align the reads to the reference genome; see TBProfiler’s original documentation for available options. bwa Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_min_af Float The minimum allele frequency to call a variant 0.1 Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_min_depth Int The minimum depth for a variant to be called. 10 Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_run_cdph_db Boolean TBProfiler uses by default the TBDB database; set this value to "true" to use the WHO v2 database with customizations for CDPH FALSE Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_run_custom_db Boolean TBProfiler uses by default the TBDB database; if you have a custom database you wish to use, you must set this value to true and provide a custom database in the tbprofiler_custom_db field FALSE Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_variant_caller String Select a different variant caller for TBProfiler to use by writing it in this block; see TBProfiler’s original documentation for available options. GATK Optional FASTA, ONT, PE, SE
merlin_magic tbprofiler_variant_calling_params String Enter additional variant calling parameters in this free text input to customize how the variant caller works in TBProfiler Optional FASTA, ONT, PE, SE
merlin_magic theiaeuk Boolean Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
merlin_magic virulencefinder_coverage_threshold Float The threshold for minimum coverage Optional FASTA, ONT, PE, SE
merlin_magic virulencefinder_database String The specific database to use virulence_ecoli Optional FASTA, ONT, PE, SE
merlin_magic virulencefinder_docker_image String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/virulencefinder:2.0.4 Optional FASTA, ONT, PE, SE
merlin_magic virulencefinder_identity_threshold Float The threshold for minimum blast identity Optional FASTA, ONT, PE, SE
nanoplot_clean cpu Int Number of CPUs to allocate to the task 4 Optional ONT
nanoplot_clean disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional ONT
nanoplot_clean docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/nanoplot:1.40.0 Optional ONT
nanoplot_clean max_length Int Maximum read length for nanoplot 100000 Optional ONT
nanoplot_clean memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional ONT
nanoplot_raw cpu Int Number of CPUs to allocate to the task 4 Optional ONT
nanoplot_raw disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional ONT
nanoplot_raw docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/nanoplot:1.40.0 Optional ONT
nanoplot_raw max_length Int Maximum read length for nanoplot 100000 Optional ONT
nanoplot_raw memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional ONT
plasmidfinder cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
plasmidfinder database String User-specified database Optional FASTA, ONT, PE, SE
plasmidfinder database_path String Path to user-specified database Optional FASTA, ONT, PE, SE
plasmidfinder disk_size Int Amount of storage (in GB) to allocate to the task 50 Optional FASTA, ONT, PE, SE
plasmidfinder docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/plasmidfinder:2.1.6 Optional FASTA, ONT, PE, SE
plasmidfinder memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
plasmidfinder method_path String Path to files for a user-specified method to use (blast or kma) Optional FASTA, ONT, PE, SE
plasmidfinder min_cov Float Threshold for minimum coverage, default threshold from PlasmidFinder CLI tool is used (0.60) 0.6 Optional FASTA, ONT, PE, SE
plasmidfinder threshold Float Threshold for mininum blast identity, default threshold from PlasmidFinder CLI tool is used (0.90). This default differs from the default of the PlasmidFinder webtool (0.95) 0.9 Optional FASTA, ONT, PE, SE
prokka compliant Boolean Forces Genbank/ENA/DDJB compliant headers in Prokka output files TRUE Optional FASTA, ONT, PE, SE
prokka cpu Int Number of CPUs to allocate to the task 8 Optional FASTA, ONT, PE, SE
prokka disk_size String Amount of storage (in GB) to allocate to the PlasmidFinder task 100 Optional FASTA, ONT, PE, SE
prokka docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/prokka:1.14.5 Optional FASTA, ONT, PE, SE
prokka memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional FASTA, ONT, PE, SE
prokka prodigal_tf File https://github.com/tseemann/prokka#option---prodigaltf Optional FASTA, ONT, PE, SE
prokka prokka_arguments String Any additional https://github.com/tseemann/prokka#command-line-options Optional FASTA, ONT, PE, SE
prokka proteins Boolean FASTA file of trusted proteins for Prokka to first use for annotations FALSE Optional FASTA, ONT, PE, SE
qc_check_task assembly_length_unambiguous Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task assembly_mean_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task combined_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task combined_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task combined_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task combined_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task cpu Int Number of CPUs to allocate to the task 4 Optional FASTA, ONT, PE, SE
qc_check_task disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
qc_check_task docker String The Docker container to use for the task "us-docker.pkg.dev/general-theiagen/theiagen/terra-tools:2023-03-16" Optional FASTA, ONT, PE, SE
qc_check_task est_coverage_clean Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task est_coverage_raw Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task kraken_human Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task kraken_human_dehosted Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task kraken_sc2 Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task kraken_sc2_dehosted Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task kraken_target_organism Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task kraken_target_organism_dehosted Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task meanbaseq_trim String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
qc_check_task midas_secondary_genus_abundance Int Internal component, do not modify Do not modify, Optional FASTA, ONT
qc_check_task midas_secondary_genus_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT
qc_check_task num_reads_clean1 Int Internal component, do not modify Do not modify, Optional FASTA
qc_check_task num_reads_clean2 Int Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task num_reads_raw1 Int Internal component, do not modify Do not modify, Optional FASTA
qc_check_task num_reads_raw2 Int Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task number_Degenerate Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task number_N Int Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task percent_reference_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task r1_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task r1_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task r1_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task r1_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA
qc_check_task r2_mean_q_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task r2_mean_q_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task r2_mean_readlength_clean Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task r2_mean_readlength_raw Float Internal component, do not modify Do not modify, Optional FASTA, ONT, SE
qc_check_task sc2_s_gene_mean_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task sc2_s_gene_percent_coverage Float Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
qc_check_task vadr_num_alerts String Internal component, do not modify Do not modify, Optional FASTA, ONT, PE, SE
quast cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
quast disk_size String Amount of storage (in GB) to allocate to the Quast task 100 Optional FASTA, ONT, PE, SE
quast docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/quast:5.0.2 Optional FASTA, ONT, PE, SE
quast memory Int Amount of memory/RAM (in GB) to allocate to the task 2 Optional FASTA, ONT, PE, SE
quast min_contig_length Int Lower threshold for a contig length in bp. Shorter contigs won’t be taken into account 500 Optional FASTA, ONT, PE, SE
raw_check_reads cpu Int Number of CPUs to allocate to the task 2 Optional ONT, PE, SE
raw_check_reads disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional ONT, PE, SE
raw_check_reads docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/bactopia/gather_samples:2.0.2 Optional ONT, PE, SE
raw_check_reads memory Int Amount of memory/RAM (in GB) to allocate to the task 2 Optional ONT, PE, SE
raw_check_reads organism String Internal component, do not modify Do not modify, Optional ONT, PE, SE
raw_check_reads workflow_series String Internal component, do not modify Do not modify, Optional ONT, PE, SE
read_QC_trim adapters File A file containing the sequence of the adapters used during library preparation, used in the BBDuk task Optional PE, SE
read_QC_trim bbduk_memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional PE, SE
read_QC_trim call_kraken Boolean Set to true to launch Kraken2; if true, you must provide a kraken_db FALSE Optional ONT, PE, SE
read_QC_trim call_midas Boolean Set to true to launch Midas TRUE Optional PE, SE
read_QC_trim downsampling_coverage Float The depth to downsample to with Rasusa 150 Optional ONT
read_QC_trim fastp_args String Additional arguments to pass to fastp -g -5 20 -3 20 Optional SE
read_QC_trim fastp_args String Additional arguments to pass to fastp "--detect_adapter_for_pe -g -5 20 -3 20 Optional PE
read_QC_trim kraken_cpu Int Number of CPUs to allocate to the task 4 Optional ONT, PE, SE
read_QC_trim kraken_db File Kraken2 database file; must be provided in call_kraken is true Optional ONT, PE, SE
read_QC_trim kraken_disk_size Int GB of storage to request for VM used to run the kraken2 task. Increase this when using large (>30GB kraken2 databases such as the "k2_standard" database) 100 Optional ONT, PE, SE
read_QC_trim kraken_memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional ONT, PE, SE
read_QC_trim max_length Int Internal component, do not modify Do not modify, Optional ONT
read_QC_trim midas_db File Midas database file gs://theiagen-large-public-files-rp/terra/theiaprok-files/midas/midas_db_v1.2.tar.gz Optional PE, SE
read_QC_trim min_length Int Internal component, do not modify Do not modify, Optional ONT
read_QC_trim phix File A file containing the phix used during Illumina sequencing; used in the BBDuk task Optional PE, SE
read_QC_trim read_processing String Read trimming software to use, either "trimmomatic" or "fastp" trimmomatic Optional PE, SE
read_QC_trim read_qc String Allows the user to decide between fastq_scan (default) and fastqc for the evaluation of read quality. fastq_scan Optional PE, SE
read_QC_trim run_prefix String Internal component, do not modify Do not modify, Optional ONT
read_QC_trim target_organism String This string is searched for in the kraken2 outputs to extract the read percentage Optional ONT, PE, SE
read_QC_trim trimmomatic_args String Additional arguments to pass to trimmomatic. "-phred33" specifies the Phred Q score encoding which is almost always phred33 with modern sequence data. -phred33 Optional PE, SE
resfinder_task acquired Boolean Set to true to tell ResFinder to identify acquired resistance genes TRUE Optional FASTA, ONT, PE, SE
resfinder_task call_pointfinder Boolean Set to true to enable detection of point mutations. FALSE Optional FASTA, ONT, PE, SE
resfinder_task cpu Int Number of CPUs to allocate to the task 2 Optional FASTA, ONT, PE, SE
resfinder_task disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional FASTA, ONT, PE, SE
resfinder_task docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/resfinder:4.1.11 Optional FASTA, ONT, PE, SE
resfinder_task memory Int Amount of memory/RAM (in GB) to allocate to the task 8 Optional FASTA, ONT, PE, SE
resfinder_task min_cov Float Minimum coverage breadth of a gene for it to be identified 0.5 Optional FASTA, ONT, PE, SE
resfinder_task min_id Float Minimum identity for ResFinder to identify a gene 0.9 Optional FASTA, ONT, PE, SE
shovill_pe assembler String Assembler to use (spades, skesa, velvet or megahit), see https://github.com/tseemann/shovill#--assembler skesa Optional PE
shovill_pe assembler_options String Assembler-specific options that you might choose, see https://github.com/tseemann/shovill#--opts Optional PE
shovill_pe cpu Int Number of CPUs to allocate to the task 4 Optional PE
shovill_pe depth Int User specified depth of coverage for downsampling (see https://github.com/tseemann/shovill#--depth and https://github.com/tseemann/shovill#main-steps) 150 Optional PE
shovill_pe disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional PE
shovill_pe docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/shovill:1.1.0 Optional PE
shovill_pe kmers String User-specified Kmer length to override choice made by Shovill, see https://github.com/tseemann/shovill#--kmers Auto Optional PE
shovill_pe memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional PE
shovill_pe min_contig_length Int Minimum contig length to keep in final assembly 200 Optional PE
shovill_pe min_coverage Float Minimum contig coverage to keep in final assembly 2 Optional PE
shovill_pe nocorr Boolean Disable correction of minor assembly errors by Shovill (see https://github.com/tseemann/shovill#main-steps) FALSE Optional PE
shovill_pe noreadcorr Boolean Disable correction of sequencing errors in reads by Shovill (seehttps://github.com/tseemann/shovill#main-steps) FALSE Optional PE
shovill_pe nostitch Boolean Disable read stitching by Shovill (see https://github.com/tseemann/shovill#main-steps) FALSE Optional PE
shovill_pe trim Boolean Enable adaptor trimming (see https://github.com/tseemann/shovill#main-steps) FALSE Optional PE
shovill_se assembler String Assembler to use (spades, skesa, velvet or megahit), see https://github.com/tseemann/shovill#--assembler skesa Optional SE
shovill_se assembler_options String Assembler-specific options that you might choose, see https://github.com/tseemann/shovill#--opts Optional SE
shovill_se cpu Int Number of CPUs to allocate to the task 4 Optional SE
shovill_se depth Int User specified depth of coverage for downsampling (see https://github.com/tseemann/shovill#--depth and https://github.com/tseemann/shovill#main-steps) 150 Optional SE
shovill_se disk_size Int Amount of storage (in GB) to allocate to the task 100 Optional SE
shovill_se docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/shovill:1.1.0 Optional SE
shovill_se kmers String User-specified Kmer length to override choice made by Shovill, see https://github.com/tseemann/shovill#--kmers auto Optional SE
shovill_se memory Int Amount of memory/RAM (in GB) to allocate to the task 16 Optional SE
shovill_se min_contig_length Int Minimum contig length to keep in final assembly 200 Optional SE
shovill_se min_coverage Float Minimum contig coverage to keep in final assembly 2 Optional SE
shovill_se nocorr Boolean Disable correction of minor assembly errors by Shovill (see https://github.com/tseemann/shovill#main-steps) FALSE Optional SE
shovill_se noreadcorr Boolean Disable correction of sequencing errors in reads by Shovill (seehttps://github.com/tseemann/shovill#main-steps) FALSE Optional SE
shovill_se trim Boolean Enable adaptor trimming (see https://github.com/tseemann/shovill#main-steps) FALSE Optional SE
ts_mlst cpu Int Number of CPUs to allocate to the task 1 Optional FASTA, ONT, PE, SE
ts_mlst disk_size Int Amount of storage (in GB) to allocate to the task 50 Optional FASTA, ONT, PE, SE
ts_mlst docker String The Docker container to use for the task us-docker.pkg.dev/general-theiagen/staphb/mlst:2.23.0-2024-08-01 Optional FASTA, ONT, PE, SE
ts_mlst memory Int Amount of memory/RAM (in GB) to allocate to the task 2 Optional FASTA, ONT, PE, SE
ts_mlst mincov Float Minimum % breadth of coverage to report an MLST allele 10 Optional FASTA, ONT, PE, SE
ts_mlst minid Float Minimum % identity to known MLST gene to report an MLST allele 95 Optional FASTA, ONT, PE, SE
ts_mlst minscore Float Minimum https://github.com/tseemann/mlst#scoring-system to assign an MLST profile 50 Optional FASTA, ONT, PE, SE
ts_mlst nopath Boolean true = use mlst --nopath. If set to false, filename paths are not stripped from FILE column in output TSV TRUE Optional FASTA, ONT, PE, SE
ts_mlst scheme String Don’t autodetect the MLST scheme; force this scheme on all inputs (see https://www.notion.so/TheiaProk-Workflow-Series-68c34aca2a0240ef94fef0acd33651b9?pvs=21 for accepted strings) None Optional FASTA, ONT, PE, SE
version_capture docker String The Docker container to use for the task "us-docker.pkg.dev/general-theiagen/theiagen/alpine-plus-bash:3.20.0" Optional FASTA, ONT, PE, SE
version_capture timezone String Set the time zone to get an accurate date of analysis (uses UTC by default) FASTA, ONT, PE, SE

Skip Characterization

Ever wanted to skip characterization? Now you can! Set the optional input perform_characterization to false to only generate an assembly and run assembly QC.

Core Tasks (performed for all taxa)

versioning: Version Capture for TheiaProk

The versioning task captures the workflow version from the GitHub (code repository) version.

Version Capture Technical details

Links
Task task_versioning.wdl
concatenate_illumina_lanes: Concatenate Multi-Lane Illumina FASTQs for Illumina only

The concatenate_illumina_lanes task concatenates Illumina FASTQ files from multiple lanes into a single file. This task only runs if the read1_lane2 input file has been provided. All read1 lanes are concatenated together and are used in subsequent tasks, as are the read2 lanes. These concatenated files are also provided as output.

Concatenate Illumina Lanes Technical Details

The concatenate_illumina_lanes task is run before any downstream steps take place.

Links
Task wf_concatenate_illumina_lanes.wdl
screen: Total Raw Read Quantification and Genome Size Estimation

The screen task ensures the quantity of sequence data is sufficient to undertake genomic analysis. It uses fastq-scan and bash commands for quantification of reads and base pairs, and mash sketching to estimate the genome size and its coverage. At each step, the results are assessed relative to pass/fail criteria and thresholds that may be defined by optional user inputs. Samples that do not meet these criteria will not be processed further by the workflow:

  1. Total number of reads: A sample will fail the read screening task if its total number of reads is less than or equal to min_reads.
  2. The proportion of basepairs reads in the forward and reverse read files: A sample will fail the read screening if fewer than min_proportion basepairs are in either the reads1 or read2 files.
  3. Number of basepairs: A sample will fail the read screening if there are fewer than min_basepairs basepairs
  4. Estimated genome size: A sample will fail the read screening if the estimated genome size is smaller than min_genome_size or bigger than max_genome_size.
  5. Estimated genome coverage: A sample will fail the read screening if the estimated genome coverage is less than the min_coverage.

Read screening is undertaken on both the raw and cleaned reads. The task may be skipped by setting the skip_screen variable to true.

Default values vary between the PE and SE workflow. The rationale for these default values can be found below. If two default values are shown, the first is for Illumina workflows and the second is for ONT.

Variable Default Value Rationale
skip_screen false Set to false to avoid waste of compute resources processing insufficient data
min_reads 7472 or 5000 Calculated from the minimum number of base pairs required for 20x coverage of Nasuia deltocephalinicola genome, the smallest known bacterial genome as of 2019-08-07 (112,091 bp), divided by 300 (the longest Illumina read length) or 5000 (estimate of ONT read length)
min_basepairs 2241820 Should be greater than 20x coverage of Nasuia deltocephalinicola, the smallest known bacterial genome (112,091 bp)
min_genome_length 100000 Based on the Nasuia deltocephalinicola genome - the smallest known bacterial genome (112,091 bp)
max_genome_length 18040666 Based on the Minicystis rosea genome, the biggest known bacterial genome (16,040,666 bp), plus an additional 2 Mbp to cater for potential extra genomic material
min_coverage 10 or 5 A bare-minimum average per base coverage across the genome required for genome characterization. Note, a higher per base coverage coverage would be required for high-quality phylogenetics.
min_proportion 40 Neither read1 nor read2 files should have less than 40% of the total number of reads. For paired-end data only

Screen Technical Details

There is a single WDL task for read screening that contains two separate sub-tasks, one used for PE data and the other for SE data. The screen task is run twice, once for raw reads and once for clean reads.

TheiaProk_Illumina_PE TheiaProk_Illumina_SE and TheiaProk_ONT
Task task_screen.wdl (PE sub-task) task_screen.wdl (SE sub-task)

Illumina Data Core Tasks

read_QC_trim: Read Quality Trimming, Adapter Removal, Quantification, and Identification

read_QC_trim is a sub-workflow within TheiaMeta that removes low-quality reads, low-quality regions of reads, and sequencing adapters to improve data quality. It uses a number of tasks, described below.

Read quality trimming

Either trimmomatic or fastp can be used for read-quality trimming. Trimmomatic is used by default. Both tools trim low-quality regions of reads with a sliding window (with a window size of trim_window_size), cutting once the average quality within the window falls below trim_quality_trim_score. They will both discard the read if it is trimmed below trim_minlen.

If fastp is selected for analysis, fastp also implements the additional read-trimming steps indicated below:

Parameter Explanation
-g enables polyG tail trimming
-5 20 enables read end-trimming
-3 20 enables read end-trimming
--detect_adapter_for_pe enables adapter-trimming only for paired-end reads

Adapter removal

The BBDuk task removes adapters from sequence reads. To do this:

  • Repair from the BBTools package reorders reads in paired fastq files to ensure the forward and reverse reads of a pair are in the same position in the two fastq files.
  • BBDuk ("Bestus Bioinformaticus" Decontamination Using Kmers) is then used to trim the adapters and filter out all reads that have a 31-mer match to PhiX, which is commonly added to Illumina sequencing runs to monitor and/or improve overall run quality.
What are adapters and why do they need to be removed?

Adapters are manufactured oligonucleotide sequences attached to DNA fragments during the library preparation process. In Illumina sequencing, these adapter sequences are required for attaching reads to flow cells. You can read more about Illumina adapters here. For genome analysis, it's important to remove these sequences since they're not actually from your sample. If you don't remove them, the downstream analysis may be affected.

Read Quantification

There are two methods for read quantification to choose from: fastq-scan (default) or fastqc. Both quantify the forward and reverse reads in FASTQ files. In TheiaProk_Illumina_PE, they also provide the total number of read pairs. This task is run once with raw reads as input and once with clean reads as input. If QC has been performed correctly, you should expect fewer clean reads than raw reads. fastqc also provides a graphical visualization of the read quality.

Read Identification (optional)

The MIDAS task is for the identification of reads to detect contamination with non-target taxa. This task is optional and turned off by default. It can be used by setting the call_midas input variable to true.

The MIDAS tool was originally designed for metagenomic sequencing data but has been co-opted for use with bacterial isolate WGS methods. It can be used to detect contamination present in raw sequencing data by estimating bacterial species abundance in bacterial isolate WGS data. If a secondary genus is detected above a relative frequency of 0.01 (1%), then the sample should fail QC and be investigated further for potential contamination.

This task is similar to those used in commercial software, BioNumerics, for estimating secondary species abundance.

How are the MIDAS output columns determined?

Example MIDAS report in the midas_report column:

species_id count_reads coverage relative_abundance
Salmonella_enterica_58156 3309 89.88006645 0.855888033
Salmonella_enterica_58266 501 11.60606061 0.110519371
Salmonella_enterica_53987 99 2.232896237 0.021262881
Citrobacter_youngae_61659 46 0.995216227 0.009477003
Escherichia_coli_58110 5 0.123668877 0.001177644

MIDAS report column descriptions:

  • species_id: species identifier
  • count_reads: number of reads mapped to marker genes
  • coverage: estimated genome-coverage (i.e. read-depth) of species in metagenome
  • relative_abundance: estimated relative abundance of species in metagenome

The value in the midas_primary_genus column is derived by ordering the rows in order of "relative_abundance" and identifying the genus of top species in the "species_id" column (Salmonella). The value in the midas_secondary_genus column is derived from the genus of the second-most prevalent genus in the "species_id" column (Citrobacter). The midas_secondary_genus_abundance column is the "relative_abundance" of the second-most prevalent genus (0.009477003). The midas_secondary_genus_coverage is the "coverage" of the second-most prevalent genus (0.995216227).

MIDAS Reference Database Overview

The MIDAS reference database is a comprehensive tool for identifying bacterial species in metagenomic and bacterial isolate WGS data. It includes several layers of genomic data, helping detect species abundance and potential contaminants.

Key Components of the MIDAS Database

  1. Species Groups:

  2. MIDAS clusters bacterial genomes based on 96.5% sequence identity, forming over 5,950 species groups from 31,007 genomes. These groups align with the gold-standard species definition (95% ANI), ensuring highly accurate species identification.

  3. Genomic Data Structure:

  4. Marker Genes: Contains 15 universal single-copy genes used to estimate species abundance.
  5. Representative Genome: Each species group has a selected representative genome, which minimizes genetic variation and aids in accurate SNP identification.

  6. Pan-genome: The database includes clusters of non-redundant genes, with options for multi-level clustering (e.g., 99%, 95%, 90% identity), enabling MIDAS to identify gene content within strains at various clustering thresholds.

  7. Taxonomic Annotation:

  8. Genomes are annotated based on consensus Latin names. Discrepancies in name assignments may occur due to factors like unclassified genomes or genus-level ambiguities.

Using the Default MIDAS Database

TheiaProk uses the pre-loaded MIDAS database in Terra (see input table for current version) by default for bacterial species detection in metagenomic data, requiring no additional setup.

How to Set Up the Default MIDAS Database

Users can also build their own custom MIDAS database if they want to include specific genomes or configurations. This custom database can replace the default MIDAS database used in Terra. To build a custom MIDAS database, follow the MIDAS GitHub guide on building a custom database. Once the database is built, users can upload it to a Google Cloud Storage bucket or Terra workkspace and provide the link to the database in the midas_db input variable.

Alternatively to MIDAS, the Kraken2 task can also be turned on through setting the call_kraken input variable as true for the identification of reads to detect contamination with non-target taxa.

Kraken2 is a bioinformatics tool originally designed for metagenomic applications. It has additionally proven valuable for validating taxonomic assignments and checking contamination of single-species (e.g. bacterial isolate) whole genome sequence data. A database must be provided if this optional module is activated, through the kraken_db optional input. A list of suggested databases can be found on Kraken2 standalone documentation.

read_QC_trim Technical Details

Links
Sub-workflow wf_read_QC_trim_pe.wdl
wf_read_QC_trim_se.wdl
Tasks task_fastp.wdl
task_trimmomatic.wdl
task_bbduk.wdl
task_fastq_scan.wdl
task_midas.wdl
task_kraken2.wdl
Software Source Code fastp; Trimmomatic; fastq-scan; MIDAS; Kraken2
Software Documentation fastp; Trimmomatic; BBDuk; fastq-scan; MIDAS; Kraken2
Original Publication(s) Trimmomatic: a flexible trimmer for Illumina sequence data
fastp: an ultra-fast all-in-one FASTQ preprocessor
An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography
Improved metagenomic analysis with Kraken 2
CG-Pipeline: Assessment of Read Quality, and Estimation of Genome Coverage

Thecg_pipeline task generates metrics about read quality and estimates the coverage of the genome using the "run_assembly_readMetrics.pl" script from CG-Pipeline. The genome coverage estimates are calculated using both using raw and cleaned reads, using either a user-provided genome_size or the estimated genome length generated by QUAST.

CG-Pipeline Technical Details

The cg_pipeline task is run twice in TheiaProk, once with raw reads, and once with clean reads.

Links
Task task_cg_pipeline.wdl
Software Source Code CG-Pipeline on GitHub
Software Documentation CG-Pipeline on GitHub
Original Publication(s) A computational genomics pipeline for prokaryotic sequencing projects
shovill: De novo Assembly

De Novo assembly will be undertaken only for samples that have sufficient read quantity and quality, as determined by the screen task assessment of clean reads.

In TheiaProk, assembly is performed using the Shovill pipeline. This undertakes the assembly with one of four assemblers (SKESA (default), SPAdes, Velvet, Megahit), but also performs a number of pre- and post-processing steps to improve the resulting genome assembly. Shovill uses an estimated genome size (see here). If this is not provided by the user as an optional input, Shovill will estimate the genome size using mash. Adaptor trimming can be undertaken with Shovill by setting the trim option to "true", but this is set to "false" by default as alternative adapter trimming is undertaken in the TheiaEuk workflow.

What is de novo assembly?

De novo assembly is the process or product of attempting to reconstruct a genome from scratch (without prior knowledge of the genome) using sequence reads. Assembly of fungal genomes from short-reads will produce multiple contigs per chromosome rather than a single contiguous sequence for each chromosome.

Shovill Technical Details

Links
TheiaEuk WDL Task task_shovill.wdl
Software Source Code Shovill on GitHub
Software Documentation Shovill on GitHub

ONT Data Core Tasks

read_QC_trim_ont: Read Quality Trimming, Quantification, and Identification

read_QC_trim_ont is a sub-workflow within TheiaProk_ONT that filters low-quality reads and trims low-quality regions of reads. It uses several tasks, described below.

Estimated genome length:

By default, an estimated genome length is set to 5 Mb, which is around 0.7 Mb higher than the average bacterial genome length, according to the information collated here. This estimate can be overwritten by the user, and is used by Rasusa and dragonflye.

Plotting and quantifying long-read sequencing data: nanoplot

Nanoplot is used for the determination of mean quality scores, read lengths, and number of reads. This task is run once with raw reads as input and once with clean reads as input. If QC has been performed correctly, you should expect fewer clean reads than raw reads.

Read subsampling: Samples are automatically randomly subsampled to 150X coverage using RASUSA.

Plasmid prediction: tiptoft is used to predict plasmid sequences directly from uncorrected long-read data. Plasmids are identified using replicon sequences used for typing from PlasmidFinder.

Read filtering: Reads are filtered by length and quality using nanoq. By default, sequences with less than 500 basepairs and quality score lower than 10 are filtered out to improve assembly accuracy.

read_QC_trim_ont Technical Details

TheiaProk_ONT calls a sub-workflow listed below, which then calls the individual tasks:

Workflow TheiaProk_ONT
Sub-workflow wf_read_QC_trim_ont.wdl
Tasks task_nanoplot.wdl task_fastq_scan.wdl task_rasusa.wdl task_nanoq.wdl task_tiptoft.wdl
Software Source Code fastq-scan, NanoPlot, RASUSA, tiptoft, nanoq
Original Publication(s) NanoPlot paper
RASUSA paper
Nanoq Paper
Tiptoft paper
dragonflye: De novo Assembly

dragonflye Technical Details

Links
Task task_dragonflye.wdl
Software Source Code dragonflye on GitHub
Software Documentation dragonflye on GitHub

Post-Assembly Tasks (performed for all taxa)

quast: Assembly Quality Assessment

QUAST stands for QUality ASsessment Tool. It evaluates genome/metagenome assemblies by computing various metrics without a reference being necessary. It includes useful metrics such as number of contigs, length of the largest contig and N50.

QUAST Technical Details

Links
Task task_quast.wdl
Software Source Code QUAST on GitHub
Software Documentation https://quast.sourceforge.net/
Original Publication(s) QUAST: quality assessment tool for genome assemblies
BUSCO: Assembly Quality Assessment

BUSCO (Benchmarking Universal Single-Copy Orthologue) attempts to quantify the completeness and contamination of an assembly to generate quality assessment metrics. It uses taxa-specific databases containing genes that are all expected to occur in the given taxa, each in a single copy. BUSCO examines the presence or absence of these genes, whether they are fragmented, and whether they are duplicated (suggestive that additional copies came from contaminants).

BUSCO notation

Here is an example of BUSCO notation: C:99.1%[S:98.9%,D:0.2%],F:0.0%,M:0.9%,n:440. There are several abbreviations used in this output:

  • Complete (C) - genes are considered "complete" when their lengths are within two standard deviations of the BUSCO group mean length.
  • Single-copy (S) - genes that are complete and have only one copy.
  • Duplicated (D) - genes that are complete and have more than one copy.
  • Fragmented (F) - genes that are only partially recovered.
  • Missing (M) - genes that were not recovered at all.
  • Number of genes examined (n) - the number of genes examined.

A high equity assembly will use the appropriate database for the taxa, have high complete (C) and single-copy (S) percentages, and low duplicated (D), fragmented (F) and missing (M) percentages.

BUSCO Technical Details

Links
Task task_busco.wdl
Software Source Code BUSCO on GitLab
Software Documentation https://busco.ezlab.org/
Orginal publication BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs
MUMmer_ANI: Average Nucleotide Identity (optional)

Average Nucleotide Identity (ANI) is a useful approach for taxonomic identification. The higher the percentage ANI of a query sequence to a given reference genome, the more likely the sequence is the same taxa as the reference.

ANI is calculated in TheiaProk using a perl script written by Lee Katz (ani-m.pl). This uses MUMmer to rapidly align entire query assemblies to one or more reference genomes. By default, TheiaProk uses a set of 43 reference genomes in RGDv2, a database containing genomes of enteric pathogens commonly sequenced by CDC EDLB & PulseNet participating laboratories. The user may also provide their own reference genome. After genome alignment with MUMmer, ani-m.pl calculates the average nucleotide identity and percent bases aligned between 2 genomes (query and reference genomes)

The default database of reference genomes used is called "Reference Genome Database version 2" AKA "RGDv2". This database is composed of 43 enteric bacteria representing 32 species and is intended for identification of enteric pathogens and common contaminants. It contains six Campylobacter spp., three Escherichia/Shigella spp., one Grimontia hollisae, six Listeria spp., one Photobacterium damselae, two Salmonella spp., and thirteen Vibrio spp.

2 Thresholds are utilized to prevent false positive hits. The ani_top_species_match will only report a genus & species match if both thresholds are surpassed. Both of these thresholds are set to match those used in BioNumerics for PulseNet organisms.

  1. ani_threshold default value of 80.0
  2. percent_bases_aligned_threshold default value of 70.0

For more information on RGDv2 database of reference genomes, please see the publication here.

MUMmer_ANI Technical Details

Links
Task task_mummer_ani.wdl
Software Source Code ani-m, MUMmer
Software Documentation ani-m, MUMmer
Original Publication(s) MUMmer4: A fast and versatile genome alignment system
Publication about RGDv2 database https://www.frontiersin.org/articles/10.3389/fmicb.2023.1225207/full
GAMBIT: Taxon Assignment

GAMBIT determines the taxon of the genome assembly using a k-mer based approach to match the assembly sequence to the closest complete genome in a database, thereby predicting its identity. Sometimes, GAMBIT can confidently designate the organism to the species level. Other times, it is more conservative and assigns it to a higher taxonomic rank.

For additional details regarding the GAMBIT tool and a list of available GAMBIT databases for analysis, please consult the GAMBIT tool documentation.

GAMBIT Technical Details

Links
Task task_gambit.wdl
Software Source Code GAMBIT on GitHub
Software Documentation GAMBIT ReadTheDocs
Original Publication(s) GAMBIT (Genomic Approximation Method for Bacterial Identification and Tracking): A methodology to rapidly leverage whole genome sequencing of bacterial isolates for clinical identification
KmerFinder: Taxon Assignment (optional)

The KmerFinder method predicts prokaryotic species based on the number of overlapping (co-occurring) k-mers, i.e., 16-mers, between the query genome and genomes in a reference database.

KmerFinder Technical Details

Links
Task task_kmerfinder.wdl
Software Source Code https://bitbucket.org/genomicepidemiology/kmerfinder
Software Documentation https://cge.food.dtu.dk/services/KmerFinder/instructions.php
Original Publication(s) Benchmarking of Methods for Genomic Taxonomy
AMRFinderPlus: AMR Genotyping (default)

NCBI's AMRFinderPlus is the default antimicrobial resistance (AMR) detection tool used in TheiaProk. ResFinder may be used alternatively and if so, AMRFinderPlus is not run.

AMRFinderPlus identifies acquired antimicrobial resistance (AMR) genes, virulence genes, and stress genes. Such AMR genes confer resistance to antibiotics, metals, biocides, heat, or acid. For some taxa (see here), AMRFinderPlus will provide taxa-specific results including filtering out genes that are almost ubiquitous in the taxa (intrinsic genes) and identifying resistance-associated point mutations. In TheiaProk, the taxon used by AMRFinderPlus is specified based on the gambit_predicted_taxon or a user-provided expected_taxon.

You can check if a gene or point mutation is in the AMRFinderPlus database here, find the sequences of reference genes here, and search the query Hidden Markov Models (HMMs) used by AMRFinderPlus to identify AMR genes and some stress and virulence proteins (here). The AMRFinderPlus database is updated frequently. You can ensure you are using the most up-to-date version by specifying the docker image as a workflow input. You might like to save this docker image as a workspace data element to make this easier.

AMRFinderPlus Technical Details

Links
Task task_amrfinderplus.wdl
Software Source Code amr on GitHub
Software Documentation https://github.com/ncbi/amr/wiki
Original Publication(s) AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence
ResFinder: AMR Genotyping & Shigella XDR phenotype prediction (alternative)

The ResFinder task is an alternative to using AMRFinderPlus for detection and identification of AMR genes and resistance-associated mutations.

This task runs the Centre for Genomic Epidemiology (CGE) ResFinder tool to identify acquired antimicrobial resistance. It can also run the CGE PointFinder tool if the call_pointfinder variable is set with to true. The databases underlying the task are different to those used by AMRFinderPlus.

The default thresholds for calling AMR genes are 90% identity and 50% coverage of the reference genes (expressed as a fraction in workflow inputs: 0.9 & 0.5). These are the same thresholds utilized in BioNumerics for calling AMR genes.

Organisms currently support by PointFinder for mutational-based predicted resistance:

  • Campylobacter coli & C. jejuni
  • Enterococcus faecalis
  • Enterococcus faecium
  • Escherichia coli & Shigella spp.
  • Helicobacter pylori
  • Neisseria gonorrhoeae
  • Klebsiella
  • Mycobacterium tuberculosis
  • Salmonella spp.
  • Staphylococcus aureus

XDR Shigella prediction

The ResFinder Task also has the ability to predict whether or not a sample meets the CDC's definition for extensively drug-resistant (XDR) Shigella.

CDC defines XDR Shigella bacteria as strains that are resistant to all commonly recommended empiric and alternative antibiotics — azithromycin, ciprofloxacin, ceftriaxone, trimethoprim-sulfamethoxazole (TMP-SMX), and ampicillin. Link to CDC HAN where this definition is found.

A sample is required to meet all 7 criteria in order to be predicted as XDR Shigella

  1. The GAMBIT task in the workflow must identify the sample as Shigella OR the user must input the word Shigella somewhere within the input String variable called expected_taxon. This requirement serves as the identification of a sample to be of the Shigella genus.
  2. Resfinder or PointFinder predicted resistance to Ampicillin
  3. Resfinder or PointFinder predicted resistance to Azithromycin
  4. Resfinder or PointFinder predicted resistance to Ciprofloxacin
  5. Resfinder or PointFinder predicted resistance to Ceftriazone
  6. Resfinder or PointFinder predicted resistance to Trimethoprim
  7. Resfinder or PointFinder predicted resistance to Sulfamethoxazole

There are 3 potential outputs for the resfinder_predicted_xdr_shigella output string:

  • Not Shigella based on gambit_predicted_taxon or user input
  • Not XDR Shigella for samples identified as Shigella by GAMBIT or user input BUT does ResFinder did not predict resistance to all 6 drugs in XDR definition
  • XDR Shigella meaning the sample was identified as Shigella and ResFinder/PointFinder did predict resistance to ceftriazone, azithromycin, ciprofloxacin, trimethoprim, sulfamethoxazole, and ampicillin.

ResFinder Technical Details

Links
Task task_resfinder.wdl
Software Source Code https://bitbucket.org/genomicepidemiology/resfinder/src/master/
Software Documentation https://bitbucket.org/genomicepidemiology/resfinder/src/master/
ResFinder database https://bitbucket.org/genomicepidemiology/resfinder_db/src/master/
PointFinder database https://bitbucket.org/genomicepidemiology/pointfinder_db/src/master/
Web-server https://cge.food.dtu.dk/services/ResFinder/
Original Publication(s) ResFinder 4.0 for predictions of phenotypes from genotypes
TS_MLST: MLST Profiling

Multilocus sequence typing (MLST) is a typing method reflecting population structure. It was developed as a portable, unambiguous method for global epidemiology using PCR, but can be applied to whole-genome sequences in silico. MLST is commonly used for pathogen surveillance, ruling out transmission, and grouping related genomes for comparative analysis.

MLST schemes are taxa-specific. Each scheme uses fragments of typically 7 housekeeping genes ("loci") and has a database associating an arbitrary number with each distinct allele of each locus. Each unique combination of alleles ("allelic profile") is assigned a numbered sequence type (ST). Significant diversification of genomes is captured by changes to the MLST loci via mutational events creating new alleles and STs, or recombinational events replacing the allele and changing the ST. Relationships between STs are based on the number of alleles they share. Clonal complexes share a scheme-specific number of alleles (usually for five of the seven loci).

MLST Limitations

Some taxa have multiple MLST schemes, and some MLST schemes are insufficiently robust.

TheiaProk uses the MLST tool developed by Torsten Seeman to assess MLST using traditional PubMLST typing schemes.

Interpretation of MLST results

Each MLST results file returns the ST and allele results for one sample. If the alleles and ST are correctly assigned, only a single integer value will be present for each. If an ST cannot be assigned, multiple integers or additional characters will be shown, representing the issues with assignment as described here.

Identifying novel alleles and STs

The MLST schemes used in TheiaProk are curated on the PubMLST website.If you identify novel alleles or allelic profiles in your data using TheiaProk's MLST task, you can get these assigned via PubMLST:

  1. Check that the novel allele or ST has not already been assigned a type on PubMLST.
    1. Download the assembly file from Terra for your sample with the novel allele or ST
    2. Go to the PubMLST webpage for the organism of interest
    3. Navigate to the organism "Typing" page
    4. Under "Query a sequence" choose "Single sequence" (e.g. this is the page for H. influenzae), select the MLST scheme under "Please select locus/scheme", upload the assembly fasta file, and click submit.
    5. Results will be returned lower on the page.
  2. If the allele or ST has not been typed previously on the PubMLST website (step 1), new allele or ST numbers can be assigned using instructions here.
Taxa with multiple MLST schemes

As default, the MLST tool automatically detects the genome's taxa to select the MLST scheme.

Some taxa have multiple MLST schemes, e.g. the Escherichia and Leptospira genera, Acinetobacter baumannii, Clostridium difficile and Streptococcus thermophilus. Only one scheme will be used by default.

Users may specify the scheme as an optional workflow input using the scheme variable of the "ts_mlst" task. Available schemes are listed here and the scheme name should be provided in quotation marks ("….").

If results from multiple MLST schemes are required for the same sample, TheiaProk can be run multiple times specifying non-default schemes. After the first run, output attributes for the workflow (i.e. output column names) must be amended to prevent results from being overwritten. Despite re-running the whole workflow, unmodified tasks will return cached outputs, preventing redundant computation.

TS_MLST Technical Details

Links
Task task_ts_mlst.wdl
Software Source Code mlst
Software Documentation mlst
Prokka: Assembly Annotation (default)

Assembly annotation is available via Prokka as default, or alternatively via Bakta. When Prokka annotation is used, Bakta is not.

Prokka is a prokaryotic genome annotation tool used to identify and describe features of interest within the genome sequence. Prokka annotates there genome by querying databases described here.

Prokka Technical Details

Links
Task task_prokka.wdl
Software Source Code prokka
Software Documentation prokka
Original Publication(s) Prokka: rapid prokaryotic genome annotation
Bakta: Assembly Annotation (alternative)

Assembly annotation is available via Bakta as an alternative to Prokka. When Bakta annotation is used, Prokka is not.

Bakta is intended for annotation of Bacteria and plasmids only, and is best described here!

Bakta Technical Details

Links
Task task_bakta.wdl
Software Source Code bakta
Software Documentation https://github.com/oschwengers/bakta
Original Publication(s) Bakta: rapid and standardized annotation of bacterial genomes via alignment-free sequence identification
PlasmidFinder: Plasmid Identification

PlasmidFinder detects plasmids in totally- or partially-sequenced genomes, and identifies the closest plasmid type in the database for typing purposes.

What are plasmids?

Plasmids are double-stranded circular or linear DNA molecules that are capable of replication independently of the chromosome and may be transferred between different species and clones. Many plasmids contain resistance or virulence genes, though some do not clearly confer an advantage to their host bacterium.

PlasmidFinder Technical Details

Links
Task task_plasmidfinder.wdl
Software Source Code https://bitbucket.org/genomicepidemiology/plasmidfinder/src/master/
Software Documentation https://bitbucket.org/genomicepidemiology/plasmidfinder/src/master/
Original Publication(s) In Silico Detection and Typing of Plasmids using PlasmidFinder and Plasmid Multilocus Sequence Typing
QC_check: Check QC Metrics Against User-Defined Thresholds (optional)

The qc_check task compares generated QC metrics against user-defined thresholds for each metric. This task will run if the user provides a qc_check_table .tsv file. If all QC metrics meet the threshold, the qc_check output variable will read QC_PASS. Otherwise, the output will read QC_NA if the task could not proceed or QC_ALERT followed by a string indicating what metric failed.

The qc_check task applies quality thresholds according to the sample taxa. The sample taxa is taken from the gambit_predicted_taxon value inferred by the GAMBIT module OR can be manually provided by the user using the expected_taxon workflow input.

Formatting the qc_check_table.tsv
  • The first column of the qc_check_table lists the taxa that the task will assess and the header of this column must be "taxon".
  • Any genus or species can be included as a row of the qc_check_table. However, these taxa must uniquely match the sample taxa, meaning that the file can include multiple species from the same genus (Vibrio_cholerae and Vibrio_vulnificus), but not both a genus row and species within that genus (Vibrio and Vibrio cholerae). The taxa should be formatted with the first letter capitalized and underscores in lieu of spaces.
  • Each subsequent column indicates a QC metric and lists a threshold for each taxa that will be checked. The column names must exactly match expected values, so we highly recommend copy and pasting from the template files below.
Template qc_check_table.tsv files

Example Purposes Only

QC threshold values shown are for example purposes only and should not be presumed to be sufficient for every dataset.

QC_Check Technical Details

Links
Task task_qc_check_phb.wdl
Taxon Tables: Copy outputs to new data tables based on taxonomic assignment (optional)

The taxon_tables module, if enabled, will copy sample data to a different data table based on the taxonomic assignment. For example, if an E. coli sample is analyzed, the module will copy the sample data to a new table for E. coli samples or add the sample data to an existing table.

To implement the taxon_tables module, provide a file indicating data table names to copy samples of each taxa to in the taxon_tables input variable. No other input variables are needed.

Formatting the taxon_tables file

The taxon_tables file must be uploaded a Google storage bucket that is accessible by Terra and should be in the format below. Briefly, the bacterial genera or species should be listed in the leftmost column with the name of the data table to copy samples of that taxon to in the rightmost column.

taxon taxon_table
Listeria_monocytogenes lmonocytogenes_specimen
Salmonella salmonella_specimen
Escherichia ecoli_specimen
Shigella shigella_specimen
Streptococcus strep_pneumo_specimen
Legionella legionella_specimen
Klebsiella klebsiella_specimen
Mycobacterium mycobacterium_specimen
Acinetobacter acinetobacter_specimen
Pseudomonas pseudomonas_specimen
Staphylococcus staphyloccus_specimen
Neisseria neisseria_specimen

There are no output columns for the taxon table task. The only output of the task is that additional data tables will appear for in the Terra workspace for samples matching a taxa in the taxon_tables file.

Abricate: Mass screening of contigs for antimicrobial and virulence genes (optional)

The abricate module, if enabled, will run abricate with the database defined in abricate_db to perform mass screening of contigs for antimicrobial resistance or virulence genes. It comes bundled with multiple databases: NCBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB. It only detects acquired resistance genes, NOT point mutations

Taxa-Specific Tasks

The TheiaProk workflows automatically activate taxa-specific sub-workflows after the identification of relevant taxa using GAMBIT. Alternatively, the user can provide the expected taxa in the expected_taxon workflow input to override the taxonomic assignment made by GAMBIT. Modules are launched for all TheiaProk workflows unless otherwise indicated.

Acinetobacter baumannii
Acinetobacter baumannii

A number of approaches are available in TheiaProk for A. baumannii characterization.

Kaptive: Capsule and lipooligosaccharide outer core typing

The cell-surface capsular polysaccharide (CPS) of Acinetobacter baumannii can be used as an epidemiological marker. CPS varies in its composition and structure and is a key determinant in virulence and a target for non-antibiotic therapeutics. Specificity for non-antibiotic therapeutics (e.g. phage therapy) bear particular significance given the extent of antibiotic resistance found in this ESKAPE pathogen.

Biosynthesis and export of CPS is encoded by genes clustering at the K locus (KL). Additional genes associated with CPS biosynthesis and export are sometimes found in other chromosomal locations. The full combination of these genes is summarized as a "K type", described as a "predicted serotype associated with the best match locus". You can read more about this here.

Previously, serotyping of A. baumannii focused on a major immunogenic polysaccharide which was considered the O antigen for the species. This serotyping approach appears to no longer be used and the serotyping scheme has not been updated in over 20 years. Nonetheless, the O-antigen polysaccharide is attached to lipooligosaccharide, and the outer core (OC) of this lipooligosaccharide varies. Biosynthesis of the outer core lipooligosaccharide is encoded by a cluster of genes at the outer core (OC) locus.

Variation in the KL and OCL can be characterized with the Kaptive tool and its associated databases of numbered A. baumannii K and OC locus variants. Kaptive takes in a genome assembly file (fasta), and assigns the K and OC locus to their numbered variants, provides K type and a description of genes in the K or OC loci and elsewhere in the chromosome, alongside metrics for quality of locus match. A description of how Kaptive works, explanations of the full output reports which are provided in the Terra data table by TheiaProk and resources for interpreting outputs are available on the Kaptive Wiki page.

Kaptive Technical Details

Links
Task task_kaptive.wdl
Software Source Code Kaptive on GitHub
Software Documentation https://github.com/katholt/Kaptive/wiki
Orginal publications Identification of Acinetobacter baumannii loci for capsular polysaccharide (KL) and lipooligosaccharide outer core (OCL) synthesis in genome assemblies using curated reference databases compatible with Kaptive
An update to the database for Acinetobacter baumannii capsular polysaccharide locus typing extends the extensive and diverse repertoire of genes found at and outside the K locus
AcinetobacterPlasmidTyping: Acinetobacter plasmid detection

Acinetobacter plasmids are not included in the PlasmidFinder database. Instead, the AcinetobacterPlasmidTyping database contains variants of the plasmid rep gene for A. baumannii plasmid identification. When matched with >/= 95 % identity, this represents a typing scheme for Acinetobacter baumannii plasmids. In TheiaProk, we use the tool abricate to query our assemblies against this database.

The bioinformatics software for querying sample assemblies against the AcinetobacterPlasmidTyping database is Abricate. The WDL task simply runs abricate, and the Acinetobacter Plasmid database and default setting of 95% minimum identity are set in the merlin magic sub-workflow.

AcinetobacterPlasmidTyping Technical Details

Links
Task task_abricate.wdl
Database and documentation https://github.com/MehradHamidian/AcinetobacterPlasmidTyping
Software Source Code and documentation abricate on GitHub
Original Publication(s) Detection and Typing of Plasmids in Acinetobacter baumannii Using rep Genes Encoding Replication Initiation Proteins
Acinetobacter MLST

Two MLST schemes are available for Acinetobacter. The Pasteur scheme is run by default, given significant problems with the Oxford scheme have been described. Should users with to alternatively or additionally use the Oxford MLST scheme, see the section above on MLST. The Oxford scheme is activated in TheiaProk with the MLST scheme input as "abaumannii".

blaOXA-51-like gene detection

The blaOXA-51-like genes, also known as oxaAB, are considered intrinsic to Acinetobacter baumannii but are not found in other Acinetobacter species. Identification of a blaOXA-51-like gene is therefore considered to confirm the species' identity as A. baumannii.

NCBI's AMRFinderPlus, which is implemented as a core module in TheiaProk, detects the blaOXA-51-like genes. This may be used to confirm the species, in addition to the GAMBIT taxon identification. The blaOXA-51-like genes act as carbapenemases when an ISAba1 is found 7 bp upstream of the gene. Detection of this IS is not currently undertaken in TheiaProk.

Escherichia or Shigella spp.
Escherichia or Shigella spp.

The Escherichia and Shigella genera are difficult to differentiate as they do not comply with genomic definitions of genera and species. Consequently, when either Escherichia or Shigella are identified by GAMBIT, all tools intended for these taxa are used.

SerotypeFinder and ECTyper are intended for analysis of E. coli. Both tools are used as there are occasional discrepancies between the serotypes predicted. This primarily arises due to differences in the databases used by each tool.

SerotypeFinder: Serotyping

SerotypeFinder, from the Centre for Genomic Epidemiology (CGE), identifies the serotype of total or partially-sequenced isolates of E. coli.

SerotypeFinder Technical Details

Links
Task task_serotypefinder.wdl
Software Source Code https://bitbucket.org/genomicepidemiology/serotypefinder/src/master/
Software Documentation https://bitbucket.org/genomicepidemiology/serotypefinder/src/master/
Original Publication(s) Rapid and Easy In Silico Serotyping of Escherichia coli Isolates by Use of Whole-Genome Sequencing Data
ECTyper: Serotyping

ECTyper is a serotyping module for E. coli. In TheiaProk, we are using assembly files as input.

ECTyper Technical Details

Links
Task task_ectyper.wdl
Software Source Code ECTyper on GitHub
Software Documentation ECTyper on GitHub
Orginal publication ECTyper: in silico Escherichia coli serotype and species prediction from raw and assembled whole-genome sequence data

VirulenceFinder identifies virulence genes in total or partial sequenced isolates of bacteria. Currently, only E. coli is supported in TheiaProk workflows.

VirulenceFinder: Virulence gene identification

VirulenceFinder in TheiaProk is only run on assembly files due to issues regarding discordant results when using read files on the web application versus the command-line.

VirulenceFinder Technical Details

Links
Task task_virulencefinder.wdl
Software Source Code VirulenceFinder
Software Documentation VirulenceFinder
Original Publication(s) Real-time whole-genome sequencing for routine typing, surveillance, and outbreak detection of verotoxigenic Escherichia co

ShigaTyper and ShigEiFinder are intended for differentiation and serotype prediction for any Shigella species and Enteroinvasive Escherichia coli (EIEC). You can read about differences between these here and here. ShigEiFinder can be run using either the assembly (default) or reads. These tasks will report if the samples are neither Shigella nor EIEC.

ShigaTyper: Shigella/EIEC differentiation and serotyping for Illumina and ONT only

ShigaTyper predicts Shigella spp. serotypes from Illumina or ONT read data. If the genome is not Shigella or EIEC, the results from this tool will state this. In the notes it provides, it also reports on the presence of ipaB which is suggestive of the presence of the "virulent invasion plasmid".

ShigaTyper Technical Details

Links
Task task_shigatyper.wdl
Software Source Code ShigaTyper on GitHub
Software Documentation https://github.com/CFSAN-Biostatistics/shigatyper
Origin publication In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification
ShigEiFinder: Shigella/EIEC differentiation and serotyping using the assembly file as input

ShigEiFinder differentiates Shigella and enteroinvasive E. coli (EIEC) using cluster-specific genes, identifies some serotypes based on the presence of O-antigen and H-antigen genes, and predicts the number of virulence plasmids. The shigeifinder task operates on assembly files.

ShigEiFinder Technical Details

Links
Task task_shigeifinder.wdl
Software Source Code ShigEiFinder on GitHub
Software Documentation ShigEiFinder on GitHub
Origin publication Cluster-specific gene markers enhance Shigella and enteroinvasive Escherichia coli in silico serotyping
ShigEiFinder_reads: Shigella/EIEC differentiation and serotyping using Illumina read files as input (optional) for Illumina data only

ShigEiFinder differentiates Shigella and enteroinvasive E. coli (EIEC) using cluster-specific genes, identifies some serotypes based on the presence of O-antigen and H-antigen genes, and predicts the number of virulence plasmids. The shigeifinder_reads task performs on read files.

ShigEiFinder_reads Technical Details

Links
Task task_shigeifinder.wdl
Software Source Code ShigEiFinder on GitHub
Software Documentation ShigEiFinder on GitHub
Origin publication Cluster-specific gene markers enhance Shigella and enteroinvasive Escherichia coli in silico serotyping

SonneiTyper is run only when GAMBIT predicts the S. sonnei species. This is the most common Shigella species in the United States.

SonneiTyper: Shigella sonnei identification, genotyping, and resistance mutation identification for Illumina and ONT data only

SonneiTyper identifies Shigella sonnei, and uses single-nucleotide variants for genotyping and prediction of quinolone resistance in gyrA (S83L, D87G, D87Y) and parC (S80I). Outputs are provided in this format.

SonneiTyper is a wrapper script around another tool, Mykrobe, that analyses the S. sonnei genomes.

SonneiTyper Technical Details

Links
Task task_sonneityping.wdl
Software Source Code Mykrobe, sonneityping
Software Documentation https://github.com/Mykrobe-tools/mykrobe/wiki, sonneityping
Original Publication(s) Global population structure and genotyping framework for genomic surveillance of the major dysentery pathogen, Shigella sonnei

Shigella XDR prediction. Please see the documentation section above for ResFinder for details regarding this taxa-specific analysis.

StxTyper: Identification and typing of Shiga toxin (Stx) genes using the assembly file as input

StxTyper screens bacterial genome assemblies for shiga toxin genes and subtypes them into known subtypes and also looks for novel subtypes in cases where the detected sequences diverge from the reference sequences.

Shiga toxin is the main virulence factor of Shiga-toxin-producing E. coli (STEC), though these genes are also found in Shigella species as well as some other genera more rarely, such as Klebsiella. Please see this review paper that describes shiga toxins in great detail.

Running StxTyper via the TheiaProk workflows

The TheiaProk workflow will automatically run stxtyper on all E. coli and Shigella spp. samples, but the user can opt-in to running the tool on any sample by setting the optional input variable call_stxtyper to true when configuring the workflow.

Generally, stxtyper looks for stxA and stxB subunits that compose a complete operon. The A subunit is longer (in amino acid length) than the B subunit. Stxtyper attempts to detect these, compare them to a database of known sequences, and type them based on amino acid composition. There typing algorithm and rules defining how to type these genes & operons will be described more completely in a publication that will be available in the future.

The stxtyper_report output TSV is provided in this output format.

Eventually this tool will be incorporated into AMRFinderPlus and will run behind-the-scenes when the user (or in this case, the TheiaProk workflow) provides the amrfinder --organism Escherichia option.

StxTyper Technical Details

Links
Task task_stxtyper.wdl
Software Source Code ncbi/stxtyper GitHub repository
Software Documentation ncbi/stxtyper GitHub repository
Original Publication(s) No publication currently available, as this is a new tool. One will be available in the future.
Haemophilus influenzae
Haemophilus influenzae
hicap: Sequence typing

Identification of cap locus serotype in Haemophilus influenzae assemblies with hicap.

The cap locus of H. influenzae is categorised into 6 different groups based on serology (a-f). There are three functionally distinct regions of the cap locus, designated region I, region II, and region III. Genes within region I (bexABCD) and region III (hcsAB) are associated with transport and post-translation modification. The region II genes encode serotype-specific proteins, with each serotype (a-f) having a distinct set of genes. cap loci are often subject to structural changes (e.g. duplication, deletion) making the process of in silico typing and characterisation of loci difficult.

hicap automates the identification of the cap locus, describes the structural layout, and performs in silico serotyping.

hicap Technical Details

Links
Task task_hicap.wdl
Software Source Code hicap on GitHub
Software Documentation hicap on GitHub
Original Publication(s) hicap: In Silico Serotyping of the Haemophilus influenzae Capsule Locus
Klebsiella spp.
Klebsiella spp.
Kleborate: Species identification, MLST, serotyping, AMR and virulence characterization

Kleborate is a tool to identify the Klebsiella species, MLST sequence type, serotype, virulence factors (ICEKp and plasmid associated), and AMR genes and mutations. Serotyping is based on the capsular (K antigen) and lipopolysaccharide (LPS) (O antigen) genes. The resistance genes identified by Kleborate are described here.

Kleborate Technical Details

Links
Task task_kleborate.wdl
Software Source Code kleborate on GitHub
Software Documentation https://github.com/katholt/Kleborate/wiki
Orginal publication A genomic surveillance framework and genotyping tool for Klebsiella pneumoniae and its related species complex
Identification of Klebsiella capsule synthesis loci from whole genome data
Legionella pneumophila
Legionella pneumophila
Legsta: Sequence-based typing

Legsta performs a sequence-based typing of Legionella pneumophila, with the intention of being used for outbreak investigations.

Legsta Technical Details

Links
Task task_legsta.wdl
Software Source Code Legsta
Software Documentation Legsta
Listeria monocytogenes
Listeria monocytogenes
LisSero: Serogroup prediction

LisSero performs serogroup prediction (1/2a, 1/2b, 1/2c, or 4b) for Listeria monocytogenes based on the presence or absence of five genes, lmo1118, lmo0737, ORF2110, ORF2819, and prs. These do not predict somatic (O) or flagellar (H) biosynthesis.

LisSero Technical Details

Links
Task task_lissero.wdl
Software Source Code LisSero
Software Documentation LisSero
Mycobacterium tuberculosis
Mycobacterium tuberculosis
TBProfiler: Lineage and drug susceptibility prediction for Illumina and ONT only

TBProfiler identifies Mycobacterium tuberculosis complex species, lineages, sub-lineages and drug resistance-associated mutations.

TBProfiler Technical Details

Links
Task task_tbprofiler.wdl
Software Source Code TBProfiler on GitHub
Software Documentation https://jodyphelan.gitbook.io/tb-profiler/
Original Publication(s) Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs
tbp-parser: Interpretation and Parsing of TBProfiler JSON outputs; requires TBProfiler and tbprofiler_additonal_outputs = true

tbp-parser adds useful drug resistance interpretation by applying expert rules and organizing the outputs from TBProfiler. Please note that this tool has not been tested on ONT data and although it is available, result accuracy should be considered carefully. To understand this module and its functions, please examine the README found with the source code here.

tbp-parser Technical Details

Links
Task task_tbp_parser.wdl
Software Source Code tbp-parser
Software Documentation tbp-parser
Clockwork: Decontamination of input read files for Illumina PE only

Clockwork decontaminates paired-end data by removing all reads that do not match the H37Rv genome or are unmapped.

Clockwork Technical Details

Links
Task task_clockwork.wdl
Software Source Code clockwork
Software Documentation https://github.com/iqbal-lab-org/clockwork/wiki
Neisseria spp.
Neisseria spp.
ngmaster: Neisseria gonorrhoeae sequence typing

NG-MAST is currently the most widely used method for epidemiological surveillance of Neisseria gonorrhoea. This tool is targeted at clinical and research microbiology laboratories that have performed WGS of N. gonorrhoeae isolates and wish to understand the molecular context of their data in comparison to previously published epidemiological studies. As WGS becomes more routinely performed, NGMASTER  has been developed to completely replace PCR-based NG-MAST, reducing time and labour costs.

The NG-STAR offers a standardized method of classifying seven well-characterized genes associated antimicrobial resistance in N. gonorrhoeae (penA, mtrR, porB, ponA, gyrA, parC and 23S rRNA) to three classes of antibiotics (cephalosporins, macrolides and fluoroquinolones).

ngmaster combines two tools: NG-MAST (in silico multi-antigen sequencing typing) and NG-STAR (sequencing typing for antimicrobial resistance).

ngmaster Technical Details

Links
Task task_ngmaster.wdl
Software Source Code ngmaster
Software Documentation ngmaster
Original Publication(s) NGMASTER: in silico multi-antigen sequence typing for Neisseria gonorrhoeae
meningotype: Neisseria meningitidis serotyping

This tool performs serotyping, MLST, finetyping (of porA, fetA, and porB), and Bexsero Antigen Sequencing Typing (BAST).

meningotype Technical Details

Links
Task task_meningotype.wdl
Software Source Code meningotype
Software Documentation meningotype
Pseudomonas aeruginosa
Pseudomonas aeruginosa
pasty: Serotyping

pasty is a tool for in silico serogrouping of Pseudomonas aeruginosa isolates. pasty was developed by Robert Petit, based on the PAst tool from the Centre for Genomic Epidemiology.

pasty Technical Details

Links
Task task_pasty.wdl
Software Source Code pasty
Software Documentation pasty
Original Publication(s) Application of Whole-Genome Sequencing Data for O-Specific Antigen Analysis and In Silico Serotyping of Pseudomonas aeruginosa Isolates.
Salmonella spp.
Salmonella spp.

Both SISTR and SeqSero2 are used for serotyping all Salmonella spp. Occasionally, the predicted serotypes may differ between SISTR and SeqSero2. When this occurs, differences are typically small and analogous, and are likely as a result of differing source databases. More information about Salmonella serovar nomenclature can be found here. For Salmonella Typhi, genotyphi is additionally run for further typing.

SISTR: Salmonella serovar prediction

SISTR performs Salmonella spp. serotype prediction using antigen gene and cgMLST gene alleles. In TheiaProk. SISTR is run on genome assemblies, and uses the default database setting (smaller "centroid" alleles or representative alleles instead of the full set of cgMLST alleles). It also runs a QC mode to determine the level of confidence in the serovar prediction (see here).

SISTR Technical Details

Links
Task task_sistr.wdl
Software Source Code SISTR
Software Documentation SISTR
Original Publication(s) The Salmonella In Silico Typing Resource (SISTR): an open web-accessible tool for rapidly typing and subtyping draft Salmonella genome assemblies.
SeqSero2: Serotyping

SeqSero2 is a tool for Salmonella serotype prediction. In the TheiaProk Illumina and ONT workflows, SeqSero2 takes in raw sequencing reads and performs targeted assembly of serotype determinant alleles, which can be used to predict serotypes including contamination between serotypes. Optionally, SeqSero2 can take the genome assembly as input.

SeqSero2 Technical Details

Links
Task task_seqsero2.wdl
Software Source Code SeqSero2
Software Documentation SeqSero2
Original Publication(s) Salmonella serotype determination utilizing high-throughput genome sequencing data.
SeqSero2: rapid and improved Salmonella serotype determination using whole genome sequencing data.
genotyphi: Salmonella Typhi lineage, clade, subclade and plasmid typing, AMR prediction for Illumina and ONT only

genotyphi is activated upon identification of the "Typhi" serotype by SISTR or SeqSero2. genotyphi divides the Salmonella enterica serovar Typhi population into detailed lineages, clades, and subclades. It also detects mutations in the quinolone-resistance determining regions, acquired antimicrobial resistance genes, plasmid replicons, and subtypes of the IncHI1 plasmid which is associated with multidrug resistance.

TheiaProk uses the Mykrobe implementation of genotyphi that takes raw sequencing reads as input.

genotyphi Technical Details

Links
Task task_genotyphi.wdl
Software Source Code genotyphi
Software Documentation https://github.com/katholt/genotyphi/blob/main/README.md#mykrobe-implementation
Orginal publication An extended genotyping framework for Salmonella enterica serovar Typhi, the cause of human typhoid
Five Years of GenoTyphi: Updates to the Global Salmonella Typhi Genotyping Framework
Staphyloccocus aureus
Staphyloccocus aureus
spatyper: Sequence typing

Given a fasta file or multiple fasta files, this script identifies the repeats and the order and generates a spa type. The repeat sequences and repeat orders found on http://spaserver2.ridom.de/ are used to identify the spa type of each enriched sequence. Ridom spa type and the genomics repeat sequence are then reported back to the user.

spatyper Technical Details

Links
Task task_spatyper.wdl
Software Source Code spatyper
Software Documentation spatyper
staphopia-sccmec: Sequence typing

This tool assigns a SCCmec type by BLAST the SCCmec primers against an assembly. staphopia-sccmecreports True for exact primer matches and False for at least 1 base pair difference. The Hamming Distance is also reported.

staphopia-sccmec Technical Details

Links
Task task_staphopiasccmec.wdl
Software Source Code staphopia-sccmec
Software Documentation staphopia-sccmec
Original Publication(s) Staphylococcus aureus viewed from the perspective of 40,000+ genomes
agrvate: Sequence typing

This tool identifies the agr locus type and reports possible variants in the agr operon. AgrVATE accepts a S. aureus genome assembly as input and performs a kmer search using an Agr-group specific kmer database to assign the Agr-group. The agr operon is then extracted using in-silico PCR and variants are called using an Agr-group specific reference operon.

agrvate Technical Details

Links
Task task_agrvate.wdl
Software Source Code agrVATE
Software Documentation agrVATE
Original Publication(s) Species-Wide Phylogenomics of the Staphylococcus aureus Agr Operon Revealed Convergent Evolution of Frameshift Mutations
Streptococcus pneumoniae
Streptococcus pneumoniae
PopPUNK: Global Pneumococcal Sequence Cluster typing

Global Pneumococcal Sequence Clusters (GPSC) define and name pneumococcal strains. GPSC designation is undertaken using the PopPUNK software and GPSC database as described in the file below, obtained from here.

:file: GPSC_README_PopPUNK2.txt

Interpreting GPSC results

  • In the *_external_clusters.csv novel clusters are assigned NA. For isolates that are assigned a novel cluster and pass QC, you can email globalpneumoseq@gmail.com to have these novel clusters added to the database.
  • Unsampled diversity in the pneumococcal population may represent missing variation that links two GPS clusters. When this is discovered, GPSCs are merged and the merge history is indicated. For example, if GPSC23 and GPSC362 merged, the GPSC would be reported as GPSC23, with a merge history of GPSC23;362.

PopPUNK Technical Details

Links
Task task_poppunk_streppneumo.wdl
GPSC database https://www.pneumogen.net/gps/#/training#command-line
Software Source Code PopPunk
Software Documentation https://poppunk.readthedocs.io/en/latest/
Original Publication(s) Fast and flexible bacterial genomic epidemiology with PopPUNK
SeroBA: Serotyping for Illumina_PE only

Streptococcus pneumoniae serotyping is performed with SeroBA.

SeroBA Technical Details

Links
Task task_seroba.wdl
Software Source Code SeroBA
Software Documentation https://sanger-pathogens.github.io/seroba/
Original Publication(s) SeroBA: rapid high-throughput serotyping of Streptococcus pneumoniae from whole genome sequence data
pbptyper: Penicillin-binding protein genotyping

The Penicillin-binding proteins (PBP) are responsible for the minimum inhibitory concentration phenotype for beta-lactam antibiotic. In Streptococcus pneumoniae, these PBP genes can be identified and typed with PBPTyper.

pbptyper Technical Details

Links
Task task_pbptyper.wdl
Software Source Code pbptyper
Software Documentation pbptyper
Original Publication(s) Penicillin-binding protein transpeptidase signatures for tracking and predicting β-lactam resistance levels in Streptococcus pneumoniae
Streptococcus pyogenes
Streptococcus pyogenes
emm-typing-tool: Sequence typing for Illumina_PE only

emm-typing of Streptococcus pyogenes raw reads. Assign emm type and subtype by querying the CDC M-type specific database.

emm-typing-tool Technical Details

Links
Task task_emmtypingtool.wdl
Software Source Code emm-typing-tool
Software Documentation emm-typing-tool
Vibrio spp.
Vibrio spp.
SRST2: Vibrio characterization for Illumina only

The SRST2 Vibrio characterization task detects sequences for Vibrio spp. characterization using Illumina sequence reads and a database of target sequence that are traditionally used in PCR methods. The sequences included in the database are as follows:

Sequence name Sequence role Purpose in database
toxR Transcriptional activator Species marker where presence identifies V. cholerae
ompW Outer Membrane Protein Species marker where presence identifies V. cholerae
ctxA Cholera toxin Indicates cholera toxin production
tcpA_classical Toxin co-pilus A allele associated with the Classical biotype Used to infer identity as Classical biotype
tcpA_ElTor Toxin co-pilus A allele associated with the El Tor biotype Used to infer identity as El Tor biotype
wbeN O antigen encoding region Used to infer identity as O1 serogroup
wbfR O antigen encoding region Used to infer identity as O139 serogroup

SRST2 Technical Details

Links
Task task_srst2_vibrio.wdl
Software Source Code srst2
Software Documentation srst2
Database Description Docker container
Abricate: Vibrio characterization

The Abricate Vibrio characterization task detects sequences for Vibrio spp. characterization using genome assemblies and the abricate "vibrio" database. The sequences included in the database are as follows:

Sequence name Sequence role Purpose in database
toxR Transcriptional activator Species marker where presence identifies V. cholerae
ompW Outer Membrane Protein Species marker where presence identifies V. cholerae
ctxA Cholera toxin Indicates cholera toxin production
tcpA_classical Toxin co-pilus A allele associated with the Classical biotype Used to infer identity as Classical biotype
tcpA_ElTor Toxin co-pilus A allele associated with the El Tor biotype Used to infer identity as El Tor biotype
wbeN O antigen encoding region Used to infer identity as O1 serogroup
wbfR O antigen encoding region Used to infer identity as O139 serogroup

Abricate Technical Details

Links
Task task_abricate_vibrio.wdl
Software Source Code abricate
Software Documentation abricate
Database Description Docker container

Outputs

Variable Type Description Workflow
abricate_abaum_database String Database of reference A. baumannii plasmid typing genes used for plasmid typing FASTA, ONT, PE, SE
abricate_abaum_docker String Docker file used for running abricate FASTA, ONT, PE, SE
abricate_abaum_plasmid_tsv File https://github.com/tseemann/abricate#output containing a row for each A. baumannii plasmid type gene found in the sample FASTA, ONT, PE, SE
abricate_abaum_plasmid_type_genes String A. baumannii Plasmid typing genes found in the sample; from GENE column in https://github.com/tseemann/abricate#output FASTA, ONT, PE, SE
abricate_abaum_version String Version of abricate used for A. baumannii plasmid typing FASTA, ONT, PE, SE
abricate_database String Database of reference used with Abricate FASTA, ONT, PE, SE
abricate_docker String Docker file used for running abricate FASTA, ONT, PE, SE
abricate_genes String Genes found in the sample; from GENE column in https://github.com/tseemann/abricate#output FASTA, ONT, PE, SE
abricate_results_tsv File https://github.com/tseemann/abricate#output containing a row for each gene found in the sample FASTA, ONT, PE, SE
abricate_version String Version of abricate used for A. baumannii plasmid typing FASTA, ONT, PE, SE
abricate_vibrio_biotype String Biotype classification according to tcpA gene sequence (Classical or ElTor) FASTA, ONT, PE, SE
abricate_vibrio_ctxA String Presence or absence of the ctxA gene FASTA, ONT, PE, SE
abricate_vibrio_detailed_tsv File Detailed ABRicate output file FASTA, ONT, PE, SE
abricate_vibrio_ompW String Presence or absence of the ompW gene FASTA, ONT, PE, SE
abricate_vibrio_serogroup String Serotype classification as O1 (wbeN gene), O139 (wbfR gene) or not detected. FASTA, ONT, PE, SE
abricate_vibrio_toxR String Presence or absence of the toxR gene FASTA, ONT, PE, SE
abricate_vibrio_version String The abricate version run FASTA, ONT, PE, SE
agrvate_agr_canonical String Canonical or non-canonical agrD FASTA, ONT, PE, SE
agrvate_agr_group String Agr group FASTA, ONT, PE, SE
agrvate_agr_match_score String Match score for agr group FASTA, ONT, PE, SE
agrvate_agr_multiple String If multiple agr groups were found FASTA, ONT, PE, SE
agrvate_agr_num_frameshifts String Number of frameshifts found in CDS of extracted agr operon FASTA, ONT, PE, SE
agrvate_docker String The docker used for AgrVATE FASTA, ONT, PE, SE
agrvate_results File A gzipped tarball of all results FASTA, ONT, PE, SE
agrvate_summary File The summary file produced FASTA, ONT, PE, SE
agrvate_version String The version of AgrVATE used FASTA, ONT, PE, SE
amrfinderplus_all_report File Output TSV file from AMRFinderPlus (described https://github.com/ncbi/amr/wiki/Running-AMRFinderPlus#fields) FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_betalactam_genes String Beta-lactam AMR genes identified by AMRFinderPlus that are known to confer resistance to beta-lactams FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_carbapenem_genes String Beta-lactam AMR genes identified by AMRFinderPlus that are known to confer resistance to carbapenem FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_cephalosporin_genes String Beta-lactam AMR genes identified by AMRFinderPlus that are known to confer resistance to cephalosporin FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_cephalothin_genes String Beta-lactam AMR genes identified by AMRFinderPlus that are known to confer resistance to cephalothin FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_genes String Beta-lactam AMR genes identified by AMRFinderPlus FASTA, ONT, PE, SE
amrfinderplus_amr_betalactam_methicillin_genes String Beta-lactam AMR genes identified by AMRFinderPlus that are known to confer resistance to methicilin FASTA, ONT, PE, SE
amrfinderplus_amr_classes String AMRFinderPlus predictions for classes of drugs that genes found in the reads are known to confer resistance to FASTA, ONT, PE, SE
amrfinderplus_amr_core_genes String AMR genes identified by AMRFinderPlus where the scope is "core" FASTA, ONT, PE, SE
amrfinderplus_amr_plus_genes String AMR genes identified by AMRFinderPlus where the scope is "plus" FASTA, ONT, PE, SE
amrfinderplus_amr_report File TSV file detailing AMR genes only, from the amrfinderplus_all_report FASTA, ONT, PE, SE
amrfinderplus_amr_subclasses String More specificity about the drugs that genes identified in the reads confer resistance to FASTA, ONT, PE, SE
amrfinderplus_db_version String AMRFinderPlus database version used FASTA, ONT, PE, SE
amrfinderplus_stress_genes String Stress genes identified by AMRFinderPlus FASTA, ONT, PE, SE
amrfinderplus_stress_report File TSV file detailing stress genes only, from the amrfinderplus_all_report FASTA, ONT, PE, SE
amrfinderplus_version String AMRFinderPlus version used FASTA, ONT, PE, SE
amrfinderplus_virulence_genes String Virulence genes identified by AMRFinderPlus FASTA, ONT, PE, SE
amrfinderplus_virulence_report File TSV file detailing virulence genes only, from the amrfinderplus_all_report FASTA, ONT, PE, SE
ani_highest_percent Float Highest ANI between query and any given reference genome (top species match) FASTA, ONT, PE, SE
ani_highest_percent_bases_aligned Float Percentage of bases aligned between query genome and top species match FASTA, ONT, PE, SE
ani_mummer_docker String Docker image used to run the ANI_mummer task FASTA, ONT, PE, SE
ani_mummer_version String Version of MUMmer used FASTA, ONT, PE, SE
ani_output_tsv File Full output TSV from ani-m FASTA, ONT, PE, SE
ani_top_species_match String Species of genome with highest ANI to query FASTA FASTA, ONT, PE, SE
assembly_fasta File https://github.com/tseemann/shovill#contigsfa ONT, PE, SE
assembly_length Int Length of assembly (total contig length) as determined by QUAST FASTA, ONT, PE, SE
bakta_gbff File Genomic GenBank format annotation file FASTA, ONT, PE, SE
bakta_gff3 File Generic Feature Format Version 3 file FASTA, ONT, PE, SE
bakta_summary File Bakta summary output TXT file FASTA, ONT, PE, SE
bakta_tsv File Annotations as simple human readable TSV FASTA, ONT, PE, SE
bakta_version String Bakta version used FASTA, ONT, PE, SE
bbduk_docker String BBDuk docker image used PE, SE
busco_database String BUSCO database used FASTA, ONT, PE, SE
busco_docker String BUSCO docker image used FASTA, ONT, PE, SE
busco_report File A plain text summary of the results in BUSCO notation FASTA, ONT, PE, SE
busco_results String BUSCO results (see https://www.notion.so/TheiaProk-Workflow-Series-68c34aca2a0240ef94fef0acd33651b9?pvs=21) FASTA, ONT, PE, SE
busco_version String BUSCO software version used FASTA, ONT, PE, SE
cg_pipeline_docker String Docker file used for running CG-Pipeline on cleaned reads PE, SE
cg_pipeline_report_clean File TSV file of read metrics from clean reads, including average read length, number of reads, and estimated genome coverage PE, SE
cg_pipeline_report_raw File TSV file of read metrics from raw reads, including average read length, number of reads, and estimated genome coverage PE, SE
clockwork_decontaminated_read1 File Decontaminated forward reads by Clockwork PE
clockwork_decontaminated_read2 File Decontaminated reverse reads by Clockwork PE
combined_mean_q_clean Float Mean quality score for the combined clean reads PE
combined_mean_q_raw Float Mean quality score for the combined raw reads PE
combined_mean_readlength_clean Float Mean read length for the combined clean reads PE
combined_mean_readlength_raw Float Mean read length for the combined raw reads PE
contigs_fastg File Assembly graph if megahit used for genome assembly PE
contigs_gfa File Assembly graph if spades used for genome assembly ONT, PE, SE
contigs_lastgraph File Assembly graph if velvet used for genome assembly PE
dragonflye_version String Version of dragonflye used for de novo assembly ONT
ectyper_predicted_serotype String Serotype predicted by ECTyper FASTA, ONT, PE, SE
ectyper_results File TSV file of evidence for ECTyper predicted serotype (see https://github.com/phac-nml/ecoli_serotyping#report-format) FASTA, ONT, PE, SE
ectyper_version String Version of ECTyper used FASTA, ONT, PE, SE
emmtypingtool_docker String Docker image for emm-typing-tool PE
emmtypingtool_emm_type String emm-type predicted PE
emmtypingtool_results_xml File XML file with emm-typing-tool resuls PE
emmtypingtool_version String Version of emm-typing-tool used PE
est_coverage_clean Float Estimated coverage calculated from clean reads and genome length ONT, PE, SE
est_coverage_raw Float Estimated coverage calculated from raw reads and genome length ONT, PE, SE
fastp_html_report File The HTML report made with fastp PE, SE
fastp_version String Version of fastp software used PE, SE
fastq_scan_clean1_json File JSON file output from fastq-scan containing summary stats about clean forward read quality and length PE, SE
fastq_scan_clean2_json File JSON file output from fastq-scan containing summary stats about clean reverse read quality and length PE
fastq_scan_num_reads_clean_pairs String Number of read pairs after cleaning as calculated by fastq_scan PE
fastq_scan_num_reads_clean1 Int Number of forward reads after cleaning as calculated by fastq_scan PE, SE
fastq_scan_num_reads_clean2 Int Number of reverse reads after cleaning as calculated by fastq_scan PE
fastq_scan_num_reads_raw_pairs String Number of input read pairs calculated by fastq_scan PE
fastq_scan_num_reads_raw1 Int Number of input forward reads calculated by fastq_scan PE, SE
fastq_scan_num_reads_raw2 Int Number of input reverse reads calculated by fastq_scan PE
fastq_scan_raw1_json File JSON file output from fastq-scan containing summary stats about raw forward read quality and length PE, SE
fastq_scan_raw2_json File JSON file output from fastq-scan containing summary stats about raw reverse read quality and length PE
fastq_scan_version String Version of fastq-scan software used PE, SE
fastqc_clean1_html File Graphical visualization of clean forward read quality from fastqc to open in an internet browser PE, SE
fastqc_clean2_html File Graphical visualization of clean reverse read quality from fastqc to open in an internet browser PE
fastqc_docker String Docker container used with fastqc PE, SE
fastqc_num_reads_clean_pairs String Number of read pairs after cleaning by fastqc PE
fastqc_num_reads_clean1 Int Number of forward reads after cleaning by fastqc PE, SE
fastqc_num_reads_clean2 Int Number of reverse reads after cleaning by fastqc PE
fastqc_num_reads_raw_pairs String Number of input read pairs by fastqc PE
fastqc_num_reads_raw1 Int Number of input reverse reads by fastqc PE, SE
fastqc_num_reads_raw2 Int Number of input reverse reads by fastqc PE
fastqc_raw1_html File Graphical visualization of raw forward read quality from fastqc to open in an internet browser PE, SE
fastqc_raw2_html File Graphical visualization of raw reverse read qualityfrom fastqc to open in an internet browser PE
fastqc_version String Version of fastqc software used PE, SE
gambit_closest_genomes File CSV file listing genomes in the GAMBIT database that are most similar to the query assembly FASTA, ONT, PE, SE
gambit_db_version String Version of GAMBIT used FASTA, ONT, PE, SE
gambit_docker String GAMBIT docker file used FASTA, ONT, PE, SE
gambit_predicted_taxon String Taxon predicted by GAMBIT FASTA, ONT, PE, SE
gambit_predicted_taxon_rank String Taxon rank of GAMBIT taxon prediction FASTA, ONT, PE, SE
gambit_report File GAMBIT report in a machine-readable format FASTA, ONT, PE, SE
gambit_version String Version of GAMBIT software used FASTA, ONT, PE, SE
genotyphi_final_genotype String Final genotype call from GenoTyphi ONT, PE, SE
genotyphi_genotype_confidence String Confidence in the final genotype call made by GenoTyphi ONT, PE, SE
genotyphi_mykrobe_json File JSON file of GenoTyphi output, described https://github.com/katholt/genotyphi#explanation-of-columns-in-the-output ONT, PE, SE
genotyphi_report_tsv File TSV file of GenoTyphi output, described https://github.com/katholt/genotyphi#explanation-of-columns-in-the-output ONT, PE, SE
genotyphi_species String Species call from Mykrobe, used to run GenoTyphi ONT, PE, SE
genotyphi_st_probes_percent_coverage Float Percentage coverage to the Typhi MLST probes ONT, PE, SE
genotyphi_version String Version of GenoTyphi used ONT, PE, SE
hicap_docker String Docker image used for hicap ONT, PE, SE
hicap_genes String cap genes identified. genes on different contigs delimited by;. truncation shown by trailing * ONT, PE, SE
hicap_results_tsv File TSV file of hicap output ONT, PE, SE
hicap_serotype String hicap serotype ONT, PE, SE
hicap_version String hicap version used ONT, PE, SE
kaptive_k_locus String Best matching K locus identified by Kaptive FASTA, ONT, PE, SE
kaptive_k_type String Best matching K type identified by Kaptive FASTA, ONT, PE, SE
kaptive_kl_confidence String Kaptive’s confidence in the KL match (see https://github.com/katholt/Kaptive/wiki/Interpreting-the-results) FASTA, ONT, PE, SE
kaptive_oc_locus String Best matching K locus identified by Kaptive FASTA, ONT, PE, SE
kaptive_ocl_confidence String Kaptive’s confidence in the OCL match (see https://github.com/katholt/Kaptive/wiki/Interpreting-the-results) FASTA, ONT, PE, SE
kaptive_output_file_k File TSV https://github.com/katholt/Kaptive/wiki/How-to-run#output-filesfrom the K locus from Kaptive FASTA, ONT, PE, SE
kaptive_output_file_oc File TSV https://github.com/katholt/Kaptive/wiki/How-to-run#output-filesfrom the OC locus from Kaptive FASTA, ONT, PE, SE
kaptive_version String Version of Kaptive used FASTA, ONT, PE, SE
kleborate_docker String Kleborate docker image used FASTA, ONT, PE, SE
kleborate_genomic_resistance_mutations String Genomic resistance mutations identifies by Kleborate FASTA, ONT, PE, SE
kleborate_key_resistance_genes String Key resistance genes identified by Kleborate FASTA, ONT, PE, SE
kleborate_klocus String Best matching K locus identified by Kleborate via Kaptive FASTA, ONT, PE, SE
kleborate_klocus_confidence String Kaptive’s confidence in the KL match (see https://github.com/katholt/Kaptive/wiki/Interpreting-the-results) FASTA, ONT, PE, SE
kleborate_ktype String Best matching K type identified by Kleborate via Kaptive FASTA, ONT, PE, SE
kleborate_mlst_sequence_type String https://github.com/katholt/Kleborate/wiki/MLST#multi-locus-sequence-typing-mlst call by Kleborate FASTA, ONT, PE, SE
kleborate_olocus String Best matching OC locus identified by Kleborate via Kaptive FASTA, ONT, PE, SE
kleborate_olocus_confidence String Kaptive’s confidence in the KL match (see https://github.com/katholt/Kaptive/wiki/Interpreting-the-results) FASTA, ONT, PE, SE
kleborate_otype String Best matching OC type identified by Kleborate via Kaptive FASTA, ONT, PE, SE
kleborate_output_file File https://github.com/katholt/Kleborate/wiki/Scores-and-counts FASTA, ONT, PE, SE
kleborate_resistance_score String Resistance score as given by kleborate FASTA, ONT, PE, SE
kleborate_version String Version of Kleborate used FASTA, ONT, PE, SE
kleborate_virulence_score String Virulence score as given by kleborate FASTA, ONT, PE, SE
kmerfinder_database String Database used to run KmerFinder FASTA, ONT, PE, SE
kmerfinder_docker String Docker image used to run KmerFinder FASTA, ONT, PE, SE
kmerfinder_query_coverage String KmerFinder’s query coverage of the top hit result FASTA, ONT, PE, SE
kmerfinder_results_tsv File Output TSV file created by KmerFinder FASTA, ONT, PE, SE
kmerfinder_template_coverage String FASTA, ONT, PE, SE
kmerfinder_top_hit String Top hit species of KmerFinder FASTA, ONT, PE, SE
kraken2_database String Kraken2 database used for the taxonomic assignment ONT, PE, SE
kraken2_docker String Docker container for Kraken2 ONT, PE, SE
kraken2_report File Report, in text format, of Kraken2 results ONT, PE, SE
kraken2_version String Kraken2 version ONT, PE, SE
legsta_predicted_sbt String Sequence based type predicted by Legsta FASTA, ONT, PE, SE
legsta_results File TSV file of legsta results (see https://github.com/tseemann/legsta#output) FASTA, ONT, PE, SE
legsta_version String Version of legsta used FASTA, ONT, PE, SE
lissero_results File TSV results file from LisSero (see https://github.com/MDU-PHL/LisSero#example-output) FASTA, ONT, PE, SE
lissero_serotype String Serotype predicted by LisSero FASTA, ONT, PE, SE
lissero_version String Version of LisSero used FASTA, ONT, PE, SE
meningotype_BAST String BAST type FASTA, ONT, PE, SE
meningotype_FetA String FetA type FASTA, ONT, PE, SE
meningotype_fHbp String fHbp type FASTA, ONT, PE, SE
meningotype_NadA String NBA type FASTA, ONT, PE, SE
meningotype_NHBA String NHBA type FASTA, ONT, PE, SE
meningotype_PorA String PorA type FASTA, ONT, PE, SE
meningotype_PorB String PorB type FASTA, ONT, PE, SE
meningotype_serogroup String Serogroup FASTA, ONT, PE, SE
meningotype_tsv File Full result file FASTA, ONT, PE, SE
meningotype_version String Version of meningotype used FASTA, ONT, PE, SE
midas_docker String MIDAS docker image used PE, SE
midas_primary_genus String Genus of most abundant species in reads PE, SE
midas_report File TSV report of full MIDAS results PE, SE
midas_secondary_genus String Genus of the next most abundant species after removing all species of the most abundant genus PE, SE
midas_secondary_genus_abundance String Relative abundance of secondary genus PE, SE
midas_secondary_genus_coverage String Absolute coverage of secondary genus PE, SE
n50_value Int N50 of assembly calculated by QUAST FASTA, ONT, PE, SE
nanoplot_docker String Docker image for nanoplot ONT
nanoplot_html_clean File Clean read file ONT
nanoplot_html_raw File Raw read file ONT
nanoplot_num_reads_clean1 Int Number of clean reads ONT
nanoplot_num_reads_raw1 Int Number of raw reads ONT
nanoplot_r1_est_coverage_clean Float Estimated coverage on the clean reads by nanoplot ONT
nanoplot_r1_est_coverage_raw Float Estimated coverage on the raw reads by nanoplot ONT
nanoplot_r1_mean_q_clean Float Mean quality score of clean forward reads ONT
nanoplot_r1_mean_q_raw Float Mean quality score of raw forward reads ONT
nanoplot_r1_mean_readlength_clean Float Mean read length of clean forward reads ONT
nanoplot_r1_mean_readlength_raw Float Mean read length of raw forward reads ONT
nanoplot_r1_median_q_clean Float Median quality score of clean forward reads ONT
nanoplot_r1_median_q_raw Float Median quality score of raw forward reads ONT
nanoplot_r1_median_readlength_clean Float Median read length of clean forward reads ONT
nanoplot_r1_median_readlength_raw Float Median read length of raw forward reads ONT
nanoplot_r1_n50_clean Float N50 of clean forward reads ONT
nanoplot_r1_n50_raw Float N50 of raw forward reads ONT
nanoplot_r1_stdev_readlength_clean Float Standard deviation read length of clean forward reads ONT
nanoplot_r1_stdev_readlength_raw Float Standard deviation read length of raw forward reads ONT
nanoplot_tsv_clean File Output TSV file created by nanoplot ONT
nanoplot_tsv_raw File Output TSV file created by nanoplot ONT
nanoplot_version String Version of nanoplot used for analysis ONT
nanoq_version String Version of nanoq used in analysis ONT
ngmaster_ngmast_porB_allele String porB allele number FASTA, ONT, PE, SE
ngmaster_ngmast_sequence_type String NG-MAST sequence type FASTA, ONT, PE, SE
ngmaster_ngmast_tbpB_allele String tbpB allele number FASTA, ONT, PE, SE
ngmaster_ngstar_23S_allele String 23S rRNA allele number FASTA, ONT, PE, SE
ngmaster_ngstar_gyrA_allele String gyrA allele number FASTA, ONT, PE, SE
ngmaster_ngstar_mtrR_allele String mtrR allele number FASTA, ONT, PE, SE
ngmaster_ngstar_parC_allele String parC allele number FASTA, ONT, PE, SE
ngmaster_ngstar_penA_allele String penA allele number FASTA, ONT, PE, SE
ngmaster_ngstar_ponA_allele String ponA allele number FASTA, ONT, PE, SE
ngmaster_ngstar_porB_allele String porB allele number FASTA, ONT, PE, SE
ngmaster_ngstar_sequence_type String NG-STAR sequence type FASTA, ONT, PE, SE
ngmaster_tsv File TSV file with NG-MAST/NG-STAR typing FASTA, ONT, PE, SE
ngmaster_version String ngmaster version FASTA, ONT, PE, SE
number_contigs Int Total number of contigs in assembly FASTA, ONT, PE, SE
pasty_all_serogroups File TSV file with details of each serogroup from pasty (see https://github.com/rpetit3/pasty#example-prefixdetailstsv) FASTA, ONT, PE, SE
pasty_blast_hits File TSV file of BLAST hits from pasty (see https://github.com/rpetit3/pasty#example-prefixblastntsv) FASTA, ONT, PE, SE
pasty_comment String FASTA, ONT, PE, SE
pasty_docker String pasty docker image used FASTA, ONT, PE, SE
pasty_serogroup String Serogroup predicted by pasty FASTA, ONT, PE, SE
pasty_serogroup_coverage Float The breadth of coverage of the O-antigen by pasty FASTA, ONT, PE, SE
pasty_serogroup_fragments Int Number of BLAST hits included in the prediction (fewer is better) FASTA, ONT, PE, SE
pasty_summary_tsv File TSV summary file of pasty outputs (see https://github.com/rpetit3/pasty#example-prefixtsv) FASTA, ONT, PE, SE
pasty_version String Version of pasty used FASTA, ONT, PE, SE
pbptyper_docker String pbptyper docker image used FASTA, ONT, PE, SE
pbptyper_pbptype_predicted_tsv File TSV file of pbptyper results (see https://github.com/rpetit3/pbptyper#example-prefixtsv) FASTA, ONT, PE, SE
pbptyper_predicted_1A_2B_2X String PBP type predicted by pbptyper FASTA, ONT, PE, SE
pbptyper_version String Version of pbptyper used FASTA, ONT, PE, SE
plasmidfinder_db_version String Version of PlasmidFnder used FASTA, ONT, PE, SE
plasmidfinder_docker String PlasmidFinder docker image used FASTA, ONT, PE, SE
plasmidfinder_plasmids String Names of plasmids identified by PlasmidFinder FASTA, ONT, PE, SE
plasmidfinder_results File Output file from PlasmidFinder in TSV format FASTA, ONT, PE, SE
plasmidfinder_seqs File Hit_in_genome_seq.fsa file produced by PlasmidFinder FASTA, ONT, PE, SE
poppunk_docker String PopPUNK docker image with GPSC database used FASTA, ONT, PE, SE
poppunk_gps_cluster String GPS cluster predicted by PopPUNK FASTA, ONT, PE, SE
poppunk_GPS_db_version String Version of GPSC database used FASTA, ONT, PE, SE
poppunk_gps_external_cluster_csv File GPSC v6 scheme designations FASTA, ONT, PE, SE
poppunk_version String Version of PopPUNK used FASTA, ONT, PE, SE
prokka_gbk File GenBank file produced from Prokka annotation of input FASTA FASTA, ONT, PE, SE
prokka_gff File Prokka output GFF3 file containing sequence and annotation (you can view this in IGV) FASTA, ONT, PE, SE
prokka_sqn File A Sequin file for GenBank submission FASTA, ONT, PE, SE
qc_check String A string that indicates whether or not the sample passes a set of pre-determined and user-provided QC thresholds FASTA, ONT, PE, SE
qc_standard File The user-provided file that contains the QC thresholds used for the QC check FASTA, ONT, PE, SE
quast_gc_percent Float The GC percent of your sample FASTA, ONT, PE, SE
quast_report File TSV report from QUAST FASTA, ONT, PE, SE
quast_version String Software version of QUAST used FASTA, ONT, PE, SE
r1_mean_q_clean Float Mean quality score of clean forward reads PE, SE
r1_mean_q_raw Float Mean quality score of raw forward reads PE, SE
r1_mean_readlength_clean Float Mean read length of clean forward reads PE, SE
r1_mean_readlength_raw Float Mean read length of raw forward reads PE, SE
r2_mean_q_clean Float Mean quality score of clean reverse reads PE
r2_mean_q_raw Float Mean quality score of raw reverse reads PE
r2_mean_readlength_clean Float Mean read length of clean reverse reads PE
r2_mean_readlength_raw Float Mean read length of raw reverse reads PE
rasusa_version String Version of RASUSA used for analysis ONT
read_screen_clean String PASS or FAIL result from clean read screening; FAIL accompanied by the reason for failure ONT, PE, SE
read_screen_raw String PASS or FAIL result from raw read screening; FAIL accompanied by thereason for failure ONT, PE, SE
read1_clean File Clean forward reads file ONT, PE, SE
read2_clean File Clean reverse reads file PE
resfinder_db_version String Version of ResFinder database FASTA, ONT, PE, SE
resfinder_docker String ResFinder docker image used FASTA, ONT, PE, SE
resfinder_pheno_table File Table containing al AMR phenotypes FASTA, ONT, PE, SE
resfinder_pheno_table_species File Table with species-specific AMR phenotypes FASTA, ONT, PE, SE
resfinder_pointfinder_pheno_table File TSV showing presence(1)/absence(0) of predicted resistance against an antibiotic class FASTA, ONT, PE, SE
resfinder_pointfinder_results File Predicted point mutations, grouped by the gene they occur in FASTA, ONT, PE, SE
resfinder_predicted_pheno_resistance String Semicolon delimited list of antimicrobial drugs and associated genes and/or point mutations. : , , ; : , ; FASTA, ONT, PE, SE
resfinder_predicted_resistance_Amp String States either Resistance or No Resistance predicted to Ampicillin based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_resistance_Axo String States either Resistance or No Resistance predicted to Ceftriaxone based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_resistance_Azm String States either Resistance or No Resistance predicted to Azithromycin based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_resistance_Cip String States either Resistance or No Resistance predicted to Ciprofloxacin based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_resistance_Smx String States either Resistance or No Resistance predicted to Sulfamethoxazole based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_resistance_Tmp String States either Resistance or No Resistance predicted to Trimothoprim based on resfinder phenotypic predictions FASTA, ONT, PE, SE
resfinder_predicted_xdr_shigella String Final prediction of XDR Shigella status based on CDC definition. Explanation can be found in the description above this table. FASTA, ONT, PE, SE
resfinder_results File Predicted resistance genes grouped by antibiotic class FASTA, ONT, PE, SE
resfinder_seqs File FASTA of resistance gene sequences from user’s input sequence FASTA, ONT, PE, SE
seq_platform String Sequencing platform input by the user FASTA, ONT, PE, SE
seqsero2_predicted_antigenic_profile String Antigenic profile predicted for Salmonella spp. by SeqSero2 ONT, PE, SE
seqsero2_predicted_contamination String Indicates whether contamination between Salmonella with different serotypes was predicted by SeqSero2 ONT, PE, SE
seqsero2_predicted_serotype String Serotype predicted by SeqSero2 ONT, PE, SE
seqsero2_report File TSV report produced by SeqSero2 ONT, PE, SE
seqsero2_version String Version of SeqSero2 used ONT, PE, SE
seroba_ariba_identity String Percentage identity between the query sequence and ARIBA-predicted serotype PE
seroba_ariba_serotype String Serotype predicted by ARIBA, via SeroBA PE
seroba_details File Detailed TSV file from SeroBA PE
seroba_docker String SeroBA docker image used PE
seroba_serotype String Serotype predicted by SeroBA PE
seroba_version String SeroBA version used PE
serotypefinder_docker String SerotypeFinder docker image used FASTA, ONT, PE, SE
serotypefinder_report File TSV report produced by SerotypeFinder FASTA, ONT, PE, SE
serotypefinder_serotype String Serotype predicted by SerotypeFinder FASTA, ONT, PE, SE
shigatyper_docker String ShigaTyper docker image used ONT, PE, SE
shigatyper_hits_tsv File Detailed TSV report from ShigaTyper (seehttps://github.com/CFSAN-Biostatistics/shigatyper#example-prefix-hitstsv) ONT, PE, SE
shigatyper_ipaB_presence_absence String Presence (+) or absence (-) of ipaB identified by ShigaTyper ONT, PE, SE
shigatyper_notes String Any notes output from ShigaTyper ONT, PE, SE
shigatyper_predicted_serotype String Serotype predicted by ShigaTyper ONT, PE, SE
shigatyper_summary_tsv File TSV summary report from ShigaTyper (see https://github.com/CFSAN-Biostatistics/shigatyper#example-prefixtsv) ONT, PE, SE
shigatyper_version String Version of ShigaTyper used ONT, PE, SE
shigeifinder_cluster String Shigella/EIEC cluster identified by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_cluster_reads String Shigella/EIEC cluster identified by ShigEiFinder using read files as inputs PE, SE
shigeifinder_docker String ShigEiFinder docker image used FASTA, ONT, PE, SE
shigeifinder_docker_reads String ShigEiFinder docker image used using read files as inputs PE, SE
shigeifinder_H_antigen String H-antigen gene identified by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_H_antigen_reads String H-antigen gene identified by ShigEiFinder using read files as inputs PE, SE
shigeifinder_ipaH_presence_absence String Presence (+) or absence (-) of ipaH identified by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_ipaH_presence_absence_reads String Presence (+) or absence (-) of ipaH identified by ShigEiFinder using read files as inputs PE, SE
shigeifinder_notes String Any notes output from ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_notes_reads String Any notes output from ShigEiFinder using read files as inputs PE, SE
shigeifinder_num_virulence_plasmid_genes String Number of virulence plasmid genes identified by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_num_virulence_plasmid_genes_reads String Number of virulence plasmid genes identified by ShigEiFinder using read files as inputs PE, SE
shigeifinder_O_antigen String O-antigen gene identified by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_O_antigen_reads String O-antigen gene identified by ShigEiFinder using read files as inputs PE, SE
shigeifinder_report File TSV report from ShigEiFinder (see https://github.com/LanLab/ShigEiFinder#shigeifinder) FASTA, ONT, PE, SE
shigeifinder_report_reads File TSV report from ShigEiFinder (see https://github.com/LanLab/ShigEiFinder#shigeifinder) using read files as inputs PE, SE
shigeifinder_serotype String Serotype predicted by ShigEiFinder FASTA, ONT, PE, SE
shigeifinder_serotype_reads String Serotype predicted by ShigEiFinder using read files as inputs PE, SE
shigeifinder_version String ShigEiFinder version used FASTA, ONT, PE, SE
shigeifinder_version_reads String ShigEiFinder version used using read files as inputs PE, SE
shovill_pe_version String Shovill version used PE
shovill_se_version String Shovill version used SE
sistr_allele_fasta File FASTA file of novel cgMLST alleles from SISTR FASTA, ONT, PE, SE
sistr_allele_json File JSON file of cgMLST allele sequences and information (see https://github.com/phac-nml/sistr_cmd#cgmlst-allele-search-results) FASTA, ONT, PE, SE
sistr_cgmlst File CSV file of the cgMLST allelic profile from SISTR (see https://github.com/phac-nml/sistr_cmd#cgmlst-allelic-profiles-output---cgmlst-profiles-cgmlst-profilescsv) FASTA, ONT, PE, SE
sistr_predicted_serotype String Serotype predicted by SISTR FASTA, ONT, PE, SE
sistr_results File TSV results file produced by SISTR (see https://github.com/phac-nml/sistr_cmd#primary-results-output--o-sistr-results) FASTA, ONT, PE, SE
sistr_version String Version of SISTR used FASTA, ONT, PE, SE
sonneityping_final_genotype String Final genotype call from Mykrobe, via sonneityper ONT, PE, SE
sonneityping_final_report_tsv File Detailed TSV report from mykrobe, via sonneityper (see https://github.com/katholt/sonneityping#example-output) ONT, PE, SE
sonneityping_genotype_confidence String Confidence in the final genotype call from sonneityper ONT, PE, SE
sonneityping_genotype_name String Human readable alias for genotype, where available provided by sonneityper ONT, PE, SE
sonneityping_mykrobe_docker String sonneityping docker image used ONT, PE, SE
sonneityping_mykrobe_report_csv File CSV report from mykrobe via sonneityper (see https://github.com/Mykrobe-tools/mykrobe/wiki/AMR-prediction-output#csv-file) ONT, PE, SE
sonneityping_mykrobe_report_json File JSON report from mykrobe via sonneityper (see https://github.com/Mykrobe-tools/mykrobe/wiki/AMR-prediction-output#json-file) ONT, PE, SE
sonneityping_mykrobe_version String Version of sonneityping used ONT, PE, SE
sonneityping_species String Species call from Mykrobe via sonneityping ONT, PE, SE
spatyper_docker String spatyper docker image used FASTA, ONT, PE, SE
spatyper_repeats String order of identified repeats FASTA, ONT, PE, SE
spatyper_tsv File TSV report with spatyper results FASTA, ONT, PE, SE
spatyper_type String spa type FASTA, ONT, PE, SE
spatyper_version String spatyper version used FASTA, ONT, PE, SE
srst2_vibrio_biotype String Biotype classification according to tcpA gene sequence (Classical or ElTor) PE, SE
srst2_vibrio_ctxA String Presence or absence of the ctxA gene PE, SE
srst2_vibrio_detailed_tsv File Detailed https://github.com/katholt/srst2 output file PE, SE
srst2_vibrio_ompW String Presence or absence of the ompW gene PE, SE
srst2_vibrio_serogroup String Serotype classification as O1 (wbeN gene), O139 (wbfR gene) or not detected. PE, SE
srst2_vibrio_toxR String Presence or absence of the toxR gene PE, SE
srst2_vibrio_version String The SRST2 version run PE, SE
staphopiasccmec_docker String staphopia-sccmec docker image used FASTA, ONT, PE, SE
staphopiasccmec_hamming_distance_tsv File staphopia-sccmec version FASTA, ONT, PE, SE
staphopiasccmec_results_tsv File sccmec types and mecA presence FASTA, ONT, PE, SE
staphopiasccmec_types_and_mecA_presence String staphopia-sccmec Hamming distance file FASTA, ONT, PE, SE
staphopiasccmec_version String staphopia-sccmec presence and absence TSV file FASTA, ONT, PE, SE
stxtyper_all_hits String Comma-separated list of matches of all types. Includes complete, partial, frameshift, internal stop, and novel hits. List is de-duplicated so multiple identical hits are only listed once. For example if 5 partial stx2 hits are detected in the genome, only 1 "stx2" will be listed in this field. To view the potential subtype for each partial hit, the user will need to view the stxtyper_report TSV file. FASTA, ONT, PE, SE
stxtyper_complete_operons String Comma-separated list of all COMPLETE operons detected by StxTyper. Show multiple hits if present in results. FASTA, ONT, PE, SE
stxtyper_docker String Name of docker image used by the stxtyper task. FASTA, ONT, PE, SE
stxtyper_novel_hits String Comma-separated list of matches that have the OPERON output of "COMPLETE_NOVEL". Possible outputs "stx1", "stx2", or "stx1,stx2" FASTA, ONT, PE, SE
stxtyper_num_hits Int Number of "hits" or rows present in the stxtyper_report TSV file FASTA, ONT, PE, SE
stxtyper_partial_hits String Possible outputs "stx1", "stx2", or "stx1,stx2". Tells the user that there was a partial hit to either the A or B subunit, but does not describe which subunit, only the possible types from the PARTIAL matches. FASTA, ONT, PE, SE
stxtyper_report File Raw results TSV file produced by StxTyper FASTA, ONT, PE, SE
stxtyper_stx_frameshifts_or_internal_stop_hits String Comma-separated list of matches that have the OPERON output of "FRAMESHIFT" or "INTERNAL_STOP". Possible outputs "stx1", "stx2", or "stx1,stx2" FASTA, ONT, PE, SE
stxtyper_version String Version of StxTyper used FASTA, ONT, PE, SE
taxon_table_status String Status of the taxon table upload FASTA, ONT, PE, SE
tbp_parser_average_genome_depth Float Optional output. Average genome depth across the reference genome ONT, PE, SE
tbp_parser_coverage_report File Optional output. TSV file with breadth of coverage of each gene associated with antimicrobial resistance in mycobacterium tuberculosis. ONT, PE, SE
tbp_parser_docker String Optional output. The docker image for tbp-parser ONT, PE
tbp_parser_genome_percent_coverage Float Optional output. The percent of the genome covered at a depth greater than the specified minimum (default 10) ONT, PE, SE
tbp_parser_laboratorian_report_csv File Optional output. Human-readable laboratorian report file containing the list of mutations found to be conferring resistance, both by WHO classification and expert rule implementation. The file contains the following columns: sample_id, tbprofiler_gene_name, tbprofiler_variant_locus_tag, tbprofiler_variant_substitution_type, tbprofiler_variant_substitution_nt, tbprofiler_variant_substitution_aa, confidence according to WHO, antimicrobial, depth, frequency, read_support, rationale ( WHO or expert rule), and warning if the coverage is below specified minimum (default 10) ONT, PE, SE
tbp_parser_lims_report_csv File Optional output. LIMS digestable CSV report containing information on resistance for a set of antimicrobials ( No resistance to X detected, The detected genetic determinant(s) have uncertain significance, resistance to X cannot be ruled out and Genetic determinant(s) associated with resistance to X detected). For each antimicrobial, the mutations found are reported in the mutation_nucleotide; (mutation_protein) format, otherwise No mutations detected is reported. ONT, PE, SE
tbp_parser_looker_report_csv File Optional output. Looker digestible CSV report containing information on resistance for a set of antimicrobials (R for resistant, S for susceptible) ONT, PE, SE
tbp_parser_version String Optional output. The version of tbp-parser ONT, PE
tbprofiler_dr_type String Drug resistance type predicted by TB-Profiler (sensitive, Pre-MDR, MDR, Pre-XDR, XDR) ONT, PE, SE
tbprofiler_main_lineage String Lineage(s) predicted by TBProfiler ONT, PE, SE
tbprofiler_median_depth Int The median depth of the H37Rv TB reference genome covered by the sample ONT, PE
tbprofiler_output_bai File Index BAM file generated by mapping sequencing reads to reference genome by TBProfiler ONT, PE, SE
tbprofiler_output_bam File BAM alignment file produced by TBProfiler ONT, PE, SE
tbprofiler_output_file File CSV report from TBProfiler ONT, PE, SE
tbprofiler_output_vcf File VCF file output from TBProfiler; the concatenation of all of the different VCF files produced during TBProfiler analysis ONT, PE, SE
tbprofiler_pct_reads_mapped Float The percentage of reads mapped to the H37Rv TB reference genome ONT, PE
tbprofiler_resistance_genes String List of resistance mutations detected by TBProfiler ONT, PE, SE
tbprofiler_sub_lineage String Sub-lineage(s) predicted by TBProfiler ONT, PE, SE
tbprofiler_version String Version of TBProfiler used ONT, PE, SE
theiaprok_fasta_analysis_date String Date of TheiaProk FASTA workflow execution FASTA
theiaprok_fasta_version String Version of TheiaProk FASTA workflow execution FASTA
theiaprok_illumina_pe_analysis_date String Date of TheiaProk PE workflow execution PE
theiaprok_illumina_pe_version String Version of TheiaProk PE workflow execution PE
theiaprok_illumina_se_analysis_date String Date of TheiaProk SE workflow execution SE
theiaprok_illumina_se_version String Version of TheiaProk SE workflow execution SE
theiaprok_ont_analysis_date String Date of TheiaProk ONT workflow execution ONT
theiaprok_ont_version String Version of TheiaProk ONT workflow execution ONT
tiptoft_plasmid_replicon_fastq File File produced by tiptoft that contains reads containing plasmid rep/inc genes ONT
tiptoft_plasmid_replicon_genes String Rep/inc genes found in sample ONT
tiptoft_version String Version of tiptoft used for analysis ONT
trimmomatic_docker String Docker image used for trimmomatic PE, SE
trimmomatic_version String Version of trimmomatic used PE, SE
ts_mlst_allelic_profile String Profile of MLST loci and allele numbers predicted by MLST FASTA, ONT, PE, SE
ts_mlst_docker String Docker image used for MLST FASTA, ONT, PE, SE
ts_mlst_novel_alleles File FASTA file containing nucleotide sequence of any alleles that are not in the MLST database used by TheiaProk FASTA, ONT, PE, SE
ts_mlst_predicted_st String ST predicted by MLST FASTA, ONT, PE, SE
ts_mlst_pubmlst_scheme String PubMLST scheme used byMLST FASTA, ONT, PE, SE
ts_mlst_results File TSV report with detailed MLST profile, including https://github.com/tseemann/mlst#missing-data FASTA, ONT, PE, SE
ts_mlst_version String Version of Torsten Seeman’s MLST tool used FASTA, ONT, PE, SE
virulencefinder_docker String VirulenceFinder docker image used FASTA, ONT, PE, SE
virulencefinder_hits String Virulence genes detected by VirulenceFinder FASTA, ONT, PE, SE
virulencefinder_report_tsv File Output TSV file created by VirulenceFinder FASTA, ONT, PE, SE