TheiaEuk Workflow Series

Quick Facts

Workflow Type	Applicable Kingdom	Last Known Changes	Command-line Compatibliity	Workflow Level
Genomic Characterization	Mycotics	PHB v2.3.0	Yes	Sample-level

TheiaEuk Workflows

The TheiaEuk_Illumina_PE workflow is for the assembly, quality assessment, and characterization of fungal genomes. It is designed to accept Illumina paired-end sequencing data as the primary input. It is currently intended only for haploid fungal genomes like Candida auris. Analyzing diploid genomes using TheiaEuk should be attempted only with expert attention to the resulting genome quality.

All input reads are processed through "core tasks" in each workflow. The core tasks include raw read quality assessment, read cleaning (quality trimming and adapter removal), de novo assembly, assembly quality assessment, and species taxon identification. For some taxa identified, taxa-specific sub-workflows will be automatically activated, undertaking additional taxa-specific characterization steps, including clade-typing and/or antifungal resistance detection.

TheiaEuk Workflow Diagram

Inputs

Input read data

The TheiaEuk_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 prior to Terra upload 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.

Terra Task Name	Variable	Type	Description	Default Value	Terra Status
theiaeuk_pe	read1	File	Unprocessed Illumina forward read file		Required
theiaeuk_pe	read2	File	Unprocessed Illumina reverse read file		Required
theiaeuk_pe	samplename	String	Name of Terra datatable		Required
busco	cpu	Int	Number of CPUs to allocate to the task	2	Optional
busco	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
busco	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/ezlabgva/busco:v5.3.2_cv1	Optional
cg_pipeline_clean	cg_pipe_opts	String	Options to pass to CG-Pipeline for clean read assessment	--fast	Optional
cg_pipeline_clean	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
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
cg_pipeline_raw	cg_pipe_opts	String	Options to pass to CG-Pipeline for clean read assessment	--fast	Optional
cg_pipeline_raw	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
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
clean_check_reads	cpu	Int	Number of CPUs to allocate to the task	2	Optional
clean_check_reads	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
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
clean_check_reads	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional
clean_check_reads	organism	String	Internal component, do not modify		Do Not Modify, Optional
clean_check_reads	workflow_series	String	Internal component, do not modify		Do Not Modify, Optional
gambit	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
gambit	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/gambit:0.5.0	Optional
merlin_magic	agrvate_docker_image	String	Internal component, do not modify	"us-docker.pkg.dev/general-theiagen/biocontainers/agrvate:1.0.2--hdfd78af_0"	Do Not Modify, Optional
merlin_magic	assembly_only	Boolean	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	call_poppunk	Boolean	Internal component, do not modify	TRUE	Do Not Modify, Optional
merlin_magic	call_shigeifinder_reads_input	Boolean	Internal component, do not modify	FALSE	Do Not Modify, Optional
merlin_magic	emmtypingtool_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/staphb/emmtypingtool:0.0.1	Do Not Modify, Optional
merlin_magic	hicap_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/biocontainers/hicap:1.0.3--py_0	Do Not Modify, Optional
merlin_magic	ont_data	Boolean	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	paired_end	Boolean	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	pasty_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/staphb/pasty:1.0.3	Do Not Modify, Optional
merlin_magic	pasty_min_coverage	Int	Internal component, do not modify	95	Do Not Modify, Optional
merlin_magic	pasty_min_pident	Int	Internal component, do not modify	95	Do Not Modify, Optional
merlin_magic	shigatyper_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/staphb/shigatyper:2.0.5	Do Not Modify, Optional
merlin_magic	shigeifinder_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/staphb/shigeifinder:1.3.5	Do Not Modify, Optional
merlin_magic	snippy_query_gene	String	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	srst2_gene_max_mismatch	Int	Internal component, do not modify	2000	Do Not Modify, Optional
merlin_magic	srst2_max_divergence	Int	Internal component, do not modify	20	Do Not Modify, Optional
merlin_magic	srst2_min_cov	Int	Internal component, do not modify	80	Do Not Modify, Optional
merlin_magic	srst2_min_depth	Int	Internal component, do not modify	5	Do Not Modify, Optional
merlin_magic	srst2_min_edge_depth	Int	Internal component, do not modify	2	Do Not Modify, Optional
merlin_magic	staphopia_sccmec_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/biocontainers/staphopia-sccmec:1.0.0--hdfd78af_0	Do Not Modify, Optional
merlin_magic	tbp_parser_coverage_threshold	Int	Internal component, do not modify	100	Do Not Modify, Optional
merlin_magic	tbp_parser_debug	Boolean	Internal component, do not modify	FALSE	Do Not Modify, Optional
merlin_magic	tbp_parser_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/theiagen/tbp-parser:2.2.2	Do Not Modify, Optional
merlin_magic	tbp_parser_min_depth	Int	Internal component, do not modify	10	Do Not Modify, Optional
merlin_magic	tbp_parser_operator	String	Internal component, do not modify	"Operator not provided"	Do Not Modify, Optional
merlin_magic	tbp_parser_output_seq_method_type	String	Internal component, do not modify	"WGS"	Do Not Modify, Optional
merlin_magic	tbp_parser_output_seq_method_type	String	Internal component, do not modify	"Sequencing method not provided"	Do Not Modify, Optional
merlin_magic	tbprofiler_additional_outputs	Boolean	Internal component, do not modify	FALSE	Do Not Modify, Optional
merlin_magic	tbprofiler_cov_frac_threshold	Int	Internal component, do not modify	1	Do Not Modify, Optional
merlin_magic	tbprofiler_custom_db	File	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	tbprofiler_mapper	String	Internal component, do not modify	bwa	Do Not Modify, Optional
merlin_magic	tbprofiler_min_af	Float	Internal component, do not modify	0.1	Do Not Modify, Optional
merlin_magic	tbprofiler_min_af_pred	Float	Internal component, do not modify	0.1	Do Not Modify, Optional
merlin_magic	tbprofiler_min_depth	Int	Internal component, do not modify	10	Do Not Modify, Optional
merlin_magic	tbprofiler_run_custom_db	Boolean	Internal component, do not modify	FALSE	Do Not Modify, Optional
merlin_magic	tbprofiler_variant_caller	String	Internal component, do not modify	freebayes	Do Not Modify, Optional
merlin_magic	tbprofiler_variant_calling_params	String	Internal component, do not modify	None	Do Not Modify, Optional
merlin_magic	virulencefinder_coverage_threshold	Float	Internal component, do not modify		Do Not Modify, Optional
merlin_magic	virulencefinder_database	String	Internal component, do not modify	"virulence_ecoli"	Do Not Modify, Optional
merlin_magic	virulencefinder_docker_image	String	Internal component, do not modify	us-docker.pkg.dev/general-theiagen/staphb/virulencefinder:2.0.4	Do Not Modify, Optional
merlin_magic	virulencefinder_identity_threshold	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	ani_highest_percent	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	ani_highest_percent_bases_aligned	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	assembly_length_unambiguous	Int	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	assembly_mean_coverage	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	cpu	Int	Number of CPUs to allocate to the task	4	Optional
qc_check_task	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
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
qc_check_task	kraken_human	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	kraken_human_dehosted	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	kraken_sc2	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	kraken_sc2_dehosted	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	kraken_target_organism	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	kraken_target_organism_dehosted	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	meanbaseq_trim	String	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	8	Optional
qc_check_task	midas_secondary_genus_abundance	Int	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	midas_secondary_genus_coverage	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	number_Degenerate	Int	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	number_N	Int	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	percent_reference_coverage	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	sc2_s_gene_mean_coverage	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	sc2_s_gene_percent_coverage	Float	Internal component, do not modify		Do Not Modify, Optional
qc_check_task	vadr_num_alerts	String	Internal component, do not modify		Do Not Modify, Optional
quast	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
quast	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/quast:5.0.2	Optional
quast	min_contig_length	Int	Minimum length of contig for QUAST	500	Optional
rasusa_task	bases	String	Explicitly set the number of bases required e.g., 4.3kb, 7Tb, 9000, 4.1MB		Optional
rasusa_task	cpu	Int	Number of CPUs to allocate to the task	4	Optional
rasusa_task	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
rasusa_task	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/rasusa:0.7.0	Optional
rasusa_task	frac	Float	Subsample to a fraction of the reads		Optional
rasusa_task	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	8	Optional
rasusa_task	num	Int	Subsample to a specific number of reads		Optional
rasusa_task	seed	Int	Random seed to use		Optional
raw_check_reads	cpu	Int	Number of CPUs to allocate to the task	2	Optional
raw_check_reads	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
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
raw_check_reads	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional
raw_check_reads	organism	String	Internal component, do not modify		Do Not Modify, Optional
raw_check_reads	workflow_series	String	Internal component, do not modify		Do Not Modify, Optional
read_QC_trim	adapters	File	File with adapter sequences to be removed		Optional
read_QC_trim	bbduk_mem	Int	Memory allocated to the BBDuk VM	8	Optional
read_QC_trim	call_kraken	Boolean	If true, Kraken2 is executed on the dataset	FALSE	Optional
read_QC_trim	call_midas	Boolean	Internal component, do not modify	FALSE	Do Not Modify, Optional
read_QC_trim	fastp_args	String	Additional arguments to pass to fastp	--detect_adapter_for_pe -g -5 20 -3 20	Optional
read_QC_trim	kraken_db	File	Database to use with kraken2		Optional
read_QC_trim	kraken_disk_size	Int	Amount of storage (in GB) to allocate to the task		Optional
read_QC_trim	kraken_memory	Int	Amount of memory/RAM (in GB) to allocate to the task		Optional
read_QC_trim	midas_db	File	Internal component, do not modify		Do Not Modify, Optional
read_QC_trim	phix	File	A file containing the phix used during Illumina sequencing; used in the BBDuk task		Optional
read_QC_trim	read_processing	String	Read trimming software to use, either "trimmomatic" or "fastp"	trimmomatic	Optional
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
read_QC_trim	target_organism	String	This string is searched for in the kraken2 outputs to extract the read percentage		Optional
read_QC_trim	trim_minlength	Int	Specifies minimum length of each read after trimming to be kept	75	Optional
read_QC_trim	trim_quality_trim_score	Int	Specifies the average quality of bases in a sliding window to be kept	20	Optional
read_QC_trim	trim_window_size	Int	Specifies window size for trimming (the number of bases to average the quality across)	10	Optional
read_QC_trim	trimmomatic_args	String	Additional arguments for trimmomatic		Optional
read_QC_trim	workflow_series	String	Internal component, do not modify		Do Not Modify, Optional
shovill_pe	assembler	String	Assembler to use (spades, skesa, velvet or megahit), see https://github.com/tseemann/shovill#--assembler	"skesa"	Optional
shovill_pe	assembler_options	String	Assembler-specific options that you might choose, see https://github.com/tseemann/shovill#--opts		Optional
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
shovill_pe	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
shovill_pe	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/shovill:1.1.0	Optional
shovill_pe	genome_length	String	Internal component, do not modify		Do Not Modify, Optional
shovill_pe	kmers	String	User-specified Kmer length to override choice made by Shovill, see https://github.com/tseemann/shovill#--kmers	auto	Optional
shovill_pe	min_contig_length	Int	Minimum contig length to keep in final assembly	200	Optional
shovill_pe	min_coverage	Float	Minimum contig coverage to keep in final assembly	2	Optional
shovill_pe	nocorr	Boolean	Disable correction of minor assembly errors by Shovill (see https://github.com/tseemann/shovill#main-steps)	FALSE	Optional
shovill_pe	noreadcorr	Boolean	Disable correction of sequencing errors in reads by Shovill (see https://github.com/tseemann/shovill#main-steps)	FALSE	Optional
shovill_pe	nostitch	Boolean	Disable read stitching by Shovill (see https://github.com/tseemann/shovill#main-steps)	FALSE	Optional
shovill_pe	trim	Boolean	Enable adaptor trimming (see https://github.com/tseemann/shovill#main-steps)	FALSE	Optional
theiaeuk_pe	busco_memory	Int	Amount of memory/RAM (in GB) to allocate to the task	8	Optional
theiaeuk_pe	call_rasusa	Boolean	If true, launch rasusa task to subsample raw reads to read depth of 150X	TRUE	Optional
theiaeuk_pe	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/1.3.0/gambit-metadata-1.3-231016.gdb	Optional
theiaeuk_pe	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/1.3.0/gambit-signatures-1.3-231016.gs	Optional
theiaeuk_pe	genome_length	Int	User-specified expected genome size to be used in genome statistics calculations		Optional
theiaeuk_pe	max_genome_size	Int	Maximum genome size able to pass read screening	50000000	Optional
theiaeuk_pe	min_basepairs	Int	Minimum number of base pairs able to pass read screening	2241820	Optional
theiaeuk_pe	min_coverage	Int	Minimum genome coverage able to pass read screening	10	Optional
theiaeuk_pe	min_genome_size	Int	Minimum genome size able to pass read screening	100000	Optional
theiaeuk_pe	min_proportion	Int	Minimum proportion of total reads in each read file to pass read screening	50	Optional
theiaeuk_pe	min_reads	Int	Minimum number of reads to pass read screening	10000	Optional
theiaeuk_pe	skip_screen	Boolean	Option to skip the read screening prior to analysis	FALSE	Optional
theiaeuk_pe	subsample_coverage	Float	Read depth for RASUSA task to subsample reads to	150	Optional
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
version_capture	timezone	String	Set the time zone to get an accurate date of analysis (uses UTC by default)		Optional

Workflow Tasks

All input reads are processed through "core tasks" in the TheiaEuk workflows. These undertake read trimming and assembly appropriate to the input data type, currently only Illumina paired-end data. TheiaEuk workflow subsequently launch default genome characterization modules for quality assessment, and additional taxa-specific characterization steps. When setting up the workflow, users may choose to use "optional tasks" or alternatives to tasks run in the workflow by default.

Core tasks

These tasks are performed regardless of organism. They perform read trimming and various quality control steps.

versioning: Version capture for TheiaEuk

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

Version Capture Technical details

	Links
Task	task_versioning.wdl

screen: Total Raw Read Quantification and Genome Size Estimation (optional, on by default)

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.

Variable	Rationale
skip_screen	Prevent the read screen from running
min_reads	Minimum number of base pairs for 20x coverage of Hansenula polymorpha divided by 300 (longest Illumina read length)
min_basepairs	Greater than 10x coverage of Hansenula polymorpha
min_genome_size	Based on the Hansenula polymorpha genome - the smallest fungal genome as of 2015-04-02 (8.97 Mbp)
max_genome_size	Based on the Cenococcum geophilum genome, the biggest pathogenic fungal genome, (177.57 Mbp)
min_coverage	A bare-minimum coverage for genome characterization. Higher coverage would be required for high-quality phylogenetics.
min_proportion	Greater than 50% reads are in the read1 file; others are in the read2 file

Screen Technical Details

There is a single WDL task for read screening. The screen task is run twice, once for raw reads and once for clean reads.

	Links
Task	task_screen.wdl

Rasusa: Read subsampling (optional, on by default)

The Rasusa task performs subsampling of the raw reads. By default, this task will subsample reads to a depth of 150X using the estimated genome length produced during the preceding raw read screen. The user can prevent the task from being launched by setting the call_rasusavariable to false.

The user can also provide an estimated genome length for the task to use for subsampling using the genome_size variable. In addition, the read depth can be modified using the subsample_coverage variable.

Rasusa Technical Details

	Links
Task	task_rasusa.wdl
Software Source Code	Rasusa on GitHub
Software Documentation	Rasusa on GitHub
Original Publication(s)	Rasusa: Randomly subsample sequencing reads to a specified coverage

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

read_QC_trim is a sub-workflow within TheiaEuk 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).

read_QC_trim Technical Details

	Links
Sub-workflow	wf_read_QC_trim_pe.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

Assembly tasks

These tasks assemble the reads into a de novo assembly and assess the quality of the assembly.

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 TheiaEuk, 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

QUAST: Assembly Quality Assessment

QUAST (QUality ASsessment Tool) evaluates genome assemblies by computing several metrics that describe the assembly quality, including the total number of bases in the assembly, the length of the largest contig in the assembly, and the assembly percentage GC content.

QUAST Technical Details

	Links
Task	task_quast.wdl
Software Source Code	QUAST on GitHub
Software Documentation	https://quast.sourceforge.net/docs/manual.html
Orginal publication	QUAST: quality assessment tool for genome assemblies

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 TheiaEuk, 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

Organism-agnostic characterization

These tasks are performed regardless of the organism and provide quality control and taxonomic assignment.

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

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

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

TheiaEuk_Illumina_PE_PHB: theiaeuk_qc_check_template.tsv

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

Organism-specific characterization

The TheiaEuk workflow automatically activates taxa-specific tasks after identification of the relevant taxa using GAMBIT. Many of these taxa-specific tasks do not require any additional inputs from the user.

Candida auris

Two tools are deployed when Candida auris is identified.

Cladetyping: clade determination

GAMBIT is used to determine the clade of the specimen by comparing the sequence to five clade-specific reference files. The output of the clade typing task will be used to specify the reference genome for the antifungal resistance detection tool.

Default reference genomes used for clade typing and antimicrobial resistance gene detection of C. auris

Clade	Genome Accession	Assembly Name	Strain	NCBI Submitter	Included mutations in AMR genes (not comprehensive)
Candida auris Clade I	GCA_002759435.2	Cand_auris_B8441_V2	B8441	Centers for Disease Control and Prevention
Candida auris Clade II	GCA_003013715.2	ASM301371v2	B11220	Centers for Disease Control and Prevention
Candida auris Clade III	GCA_002775015.1	Cand_auris_B11221_V1	B11221	Centers for Disease Control and Prevention	ERG11 V125A/F126L
Candida auris Clade IV	GCA_003014415.1	Cand_auris_B11243	B11243	Centers for Disease Control and Prevention	ERG11 Y132F
Candida auris Clade V	GCA_016809505.1	ASM1680950v1	IFRC2087	Centers for Disease Control and Prevention

Cladetyping Technical Details

	Links
Task	task_cauris_cladetyping.wdl
Software Source Code	GAMBIT on GitHub
Software Documentation	GAMBIT Overview
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 TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization

Snippy Variants: antifungal resistance detection

To detect mutations that may confer antifungal resistance, Snippy is used to find all variants relative to the clade-specific reference, then these variants are queried for product names associated with resistance.

The genes in which there are known resistance-conferring mutations for this pathogen are:

• FKS1
• ERG11 (lanosterol 14-alpha demethylase)
• FUR1 (uracil phosphoribosyltransferase)

We query Snippy results to see if any mutations were identified in those genes. By default, we automatically check for the following loci (which can be overwritten by the user). You will find the mutations next to the locus tag in the theiaeuk_snippy_variants_hits column corresponding gene name (see below):

TheiaEuk Search Term	Corresponding Gene Name
B9J08_005340	ERG6
B9J08_000401	FLO8
B9J08_005343	Hypothetical protein (PSK74852)
B9J08_003102	MEC3
B9J08_003737	ERG3
lanosterol.14-alpha.demethylase	ERG11
uracil.phosphoribosyltransferase	FUR1
FKS1	FKS1

For example, one sample may have the following output for the theiaeuk_snippy_variants_hits column:

lanosterol.14-alpha.demethylase: lanosterol 14-alpha demethylase (missense_variant c.428A>G p.Lys143Arg; C:266 T:0),B9J08_000401: hypothetical protein (stop_gained c.424C>T p.Gln142*; A:70 G:0)

Based on this, we can tell that ERG11 has a missense variant at position 143 (Lysine to Arginine) and B9J08_000401 (which is FLO8) has a stop-gained variant at position 142 (Glutamine to Stop).

Known resistance-conferring mutations for Candida auris

Mutations in these genes that are known to confer resistance are shown below

Organism	Found in	Gene name	Gene locus	AA mutation	Drug	Reference
Candida auris	Human	ERG11		Y132F	Fluconazole	Simultaneous Emergence of Multidrug-Resistant Candida auris on 3 Continents Confirmed by Whole-Genome Sequencing and Epidemiological Analyses
Candida auris	Human	ERG11		K143R	Fluconazole	Simultaneous Emergence of Multidrug-Resistant Candida auris on 3 Continents Confirmed by Whole-Genome Sequencing and Epidemiological Analyses
Candida auris	Human	ERG11		F126T	Fluconazole	Simultaneous Emergence of Multidrug-Resistant Candida auris on 3 Continents Confirmed by Whole-Genome Sequencing and Epidemiological Analyses
Candida auris	Human	FKS1		S639P	Micafungin	Activity of CD101, a long-acting echinocandin, against clinical isolates of Candida auris
Candida auris	Human	FKS1		S639P	Caspofungin	Activity of CD101, a long-acting echinocandin, against clinical isolates of Candida auris
Candida auris	Human	FKS1		S639P	Anidulafungin	Activity of CD101, a long-acting echinocandin, against clinical isolates of Candida auris
Candida auris	Human	FKS1		S639F	Micafungin	A multicentre study of antifungal susceptibility patterns among 350 Candida auris isolates (2009–17) in India: role of the ERG11 and FKS1 genes in azole and echinocandin resistance
Candida auris	Human	FKS1		S639F	Caspofungin	A multicentre study of antifungal susceptibility patterns among 350 Candida auris isolates (2009–17) in India: role of the ERG11 and FKS1 genes in azole and echinocandin resistance
Candida auris	Human	FKS1		S639F	Anidulafungin	A multicentre study of antifungal susceptibility patterns among 350 Candida auris isolates (2009–17) in India: role of the ERG11 and FKS1 genes in azole and echinocandin resistance
Candida auris	Human	FUR1	CAMJ_004922	F211I	5-flucytosine	Genomic epidemiology of the UK outbreak of the emerging human fungal pathogen Candida auris

Snippy Variants Technical Details

	Links
Task	task_snippy_variants.wdl task_snippy_gene_query.wdl
Software Source Code	Snippy on GitHub
Software Documentation	Snippy on GitHub

Candida albicans

When this species is detected by the taxon ID tool, an antifungal resistance detection task is deployed.

Snippy Variants: antifungal resistance detection

To detect mutations that may confer antifungal resistance, Snippy is used to find all variants relative to the clade-specific reference, and these variants are queried for product names associated with resistance.

The genes in which there are known resistance-conferring mutations for this pathogen are:

• ERG11
• GCS1 (FKS1)
• FUR1
• RTA2

We query Snippy results to see if any mutations were identified in those genes. By default, we automatically check for the following loci (which can be overwritten by the user). You will find the mutations next to the locus tag in the theiaeuk_snippy_variants_hits column corresponding gene name (see below):

TheiaEuk Search Term	Corresponding Gene Name
ERG11	ERG11
GCS1	FKS1
FUR1	FUR1
RTA2	RTA2

Snippy Variants Technical Details

	Links
Task	task_snippy_variants.wdl task_snippy_gene_query.wdl
Software Source Code	Snippy on GitHub
Software Documentation	Snippy on GitHub

Aspergillus fumigatus

When this species is detected by the taxon ID tool an antifungal resistance detection task is deployed.

Snippy Variants: antifungal resistance detection

To detect mutations that may confer antifungal resistance, Snippy is used to find all variants relative to the clade-specific reference, and these variants are queried for product names associated with resistance.

The genes in which there are known resistance-conferring mutations for this pathogen are:

• Cyp51A
• HapE
• COX10 (AFUA_4G08340)

We query Snippy results to see if any mutations were identified in those genes. By default, we automatically check for the following loci (which can be overwritten by the user). You will find the mutations next to the locus tag in the theiaeuk_snippy_variants_hits column corresponding gene name (see below):

TheiaEuk Search Term	Corresponding Gene Name
Cyp51A	Cyp51A
HapE	HapE
AFUA_4G08340	COX10

Snippy Variants Technical Details

	Links
Task	task_snippy_variants.wdl task_snippy_gene_query.wdl
Software Source Code	Snippy on GitHub
Software Documentation	Snippy on GitHub

Cryptococcus neoformans

When this species is detected by the taxon ID tool an antifungal resistance detection task is deployed.

Snippy Variants: antifungal resistance detection

To detect mutations that may confer antifungal resistance, Snippy is used to find all variants relative to the clade-specific reference, and these variants are queried for product names associated with resistance.

The genes in which there are known resistance-conferring mutations for this pathogen are:

• ERG11 (CNA00300)

We query Snippy results to see if any mutations were identified in those genes. By default, we automatically check for the following loci (which can be overwritten by the user). You will find the mutations next to the locus tag in the theiaeuk_snippy_variants_hits column corresponding gene name (see below):

TheiaEuk Search Term	Corresponding Gene Name
CNA00300	ERG11

Snippy Variants Technical Details

	Links
Task	task_snippy_variants.wdl task_snippy_gene_query.wdl
Software Source Code	Snippy on GitHub
Software Documentation	Snippy on GitHub

Outputs

Variable	Type	Description
cg_pipeline_docker	String	Docker file used for running CG-Pipeline on cleaned reads
cg_pipeline_report	File	TSV file of read metrics from raw reads, including average read length, number of reads, and estimated genome coverage
est_coverage_clean	Float	Estimated coverage calculated from clean reads and genome length
est_coverage_raw	Float	Estimated coverage calculated from raw reads and genome length
fastq_scan_clean1_json	File	JSON file output from fastq-scan containing summary stats about clean forward read quality and length
fastq_scan_clean2_json	File	JSON file output from fastq-scan containing summary stats about clean reverse read quality and length
fastq_scan_raw1_json	File	JSON file output from fastq-scan containing summary stats about raw forward read quality and length
fastq_scan_raw2_json	File	JSON file output from fastq-scan containing summary stats about raw reverse read quality and length
r1_mean_q_clean	Float	Mean quality score of clean forward reads
r1_mean_q_raw	Float	Mean quality score of raw forward reads
r2_mean_q_clean	Float	Mean quality score of clean reverse reads
r2_mean_q_raw	Float	Mean quality score of raw reverse reads
fastq_scan_version	String	Version of fastq-scan software used
gambit_closest_genomes	File	CSV file listing genomes in the GAMBIT database that are most similar to the query assembly
gambit_db_version	String	Version of GAMBIT used
gambit_docker	String	GAMBIT docker file used
gambit_predicted_taxon	String	Taxon predicted by GAMBIT
gambit_predicted_taxon_rank	String	Taxon rank of GAMBIT taxon prediction
gambit_report	File	GAMBIT report in a machine-readable format
gambit_version	String	Version of GAMBIT software used
assembly_length	Int	Length of assembly (total contig length) as determined by QUAST
n50_value	Int	N50 of assembly calculated by QUAST
number_contigs	Int	Total number of contigs in assembly
quast_report	File	TSV report from QUAST
quast_version	String	Software version of QUAST used
rasusa_version	String	Version of rasusa used
read1_subsampled	File	Subsampled read1 file
read2_subsampled	File	Subsampled read2 file
bbduk_docker	String	BBDuk docker image used
fastp_version	String	Version of fastp software used
read1_clean	File	Clean forward reads file
read2_clean	File	Clean reverse reads file
num_reads_clean_pairs	String	Number of read pairs after cleaning
num_reads_clean1	Int	Number of forward reads after cleaning
num_reads_clean2	Int	Number of reverse reads after cleaning
num_reads_raw_pairs	String	Number of input read pairs
num_reads_raw1	Int	Number of input forward reads
num_reads_raw2	Int	Number of input reverse reads
trimmomatic_version	String	Version of trimmomatic used
clean_read_screen	String	PASS or FAIL result from clean read screening; FAIL accompanied by the reason for failure
raw_read_screen	String	PASS or FAIL result from raw read screening; FAIL accompanied by thereason for failure
assembly_fasta	File	https://github.com/tseemann/shovill#contigsfa
contigs_fastg	File	Assembly graph if megahit used for genome assembly
contigs_gfa	File	Assembly graph if spades used for genome assembly
contigs_lastgraph	File	Assembly graph if velvet used for genome assembly
shovill_pe_version	String	Shovill version used
theiaeuk_snippy_variants_bam	File	BAM file produced by the snippy module
theiaeuk_snippy_variants_gene_query_results	File	File containing all lines from variants file matching gene query terms
theiaeuk_snippy_variants_hits	String	String of all variant file entries matching gene query term
theiaeuk_snippy_variants_outdir_tarball	File	Tar compressed file containing full snippy output directory
theiaeuk_snippy_variants_query	String	The gene query term(s) used to search variant
theiaeuk_snippy_variants_query_check	String	Were the gene query terms present in the refence annotated genome file
theiaeuk_snippy_variants_reference_genome	File	The reference genome used in the alignment and variant calling
theiaeuk_snippy_variants_results	File	The variants file produced by snippy
theiaeuk_snippy_variants_summary	File	A file summarizing the variants detected by snippy
theiaeuk_snippy_variants_version	String	The version of the snippy_variants module being used
seq_platform	String	Sequencing platform inout by the user
theiaeuk_illumina_pe_analysis_date	String	Date of TheiaProk workflow execution
theiaeuk_illumina_pe_version	String	TheiaProk workflow version used