Snippy_Tree¶

Quick Facts¶

Workflow Type	Applicable Kingdom	Last Known Changes	Command-line Compatibility	Workflow Level
Phylogenetic Construction	Bacteria	PHB v2.3.0	Yes; some optional features incompatible	Set-level

Snippy_Tree_PHB¶

Snippy_Tree is a workflow for generating high-quality bacterial phylogenies. It produces a phylogenetic tree and pairwise SNP-distance matrix, with the option to summarize additional metadata to visualize with the tree.

The tree produced by Snippy_Tree will always be a maximum-likelihood phylogeny using a reference-based alignment. There are key options for whether to:

Generate a core-genome or whole-genome phylogeny (core_genome)
Mask specified regions of the genome with a bed file (e.g. known repetitive regions for TB) (bed_file)
Mask recombination (use_gubbins)
Decide which nucleotide substitution model to use

Inputs¶

Snippy_Tree is intended to be run after the Snippy_Variants workflow. It is a set-level workflow that takes in an array of directories generated by the Snippy_Variants workflow, which must be run for each sample that you wish to include in the phylogenetic tree. You should ensure that for all samples included in the phylogeny, Snippy_Variants has been run with identical inputs including the same reference genome. When running the Snippy_Tree workflow, you will need to provide the same reference genome that you used when running Snippy_Variants. Snippy_Variants and Snippy_Tree can both automatically be run by using the Snippy_Streamline workflow.

Sequencing data used in the Snippy_Tree workflow must:

Be Illumina reads
Be generated by unbiased whole genome shotgun sequencing
Pass appropriate QC thresholds for the taxa to ensure that the reads represent reasonably complete genomes that are free of contamination from other taxa or cross-contamination of the same taxa.
If masking recombination with Gubbins, input data should represent whole genomes from the same strain/lineage (e.g. MLST) that share a recent common ancestor.

Guidance for optional inputs

Several core and optional tasks can be used to generate the Snippy phylogenetic tree, making it highly flexible and suited to a wide range of datasets. You will need to decide which tasks to use depending on the genomes that you are analyzing. Some guidelines for the optional tasks to use for different genome types are provided below.

Default settings (suitable for most bacteria)

The default settings are as follows and are suitable for generating phylogenies for most bacteria

core_genome = true (creates core genome phylogeny)
use_gubbins = true (recombination masked)
nucleotide substitution model will be defined by IQTree's Model Finder

Phylogenies of Mycobacterium tuberculosis complex

Phylogenies of MTBC are typically constructed

Using the H37Rv reference genome
- reference_genome_file = gs://theiagen-public-files-rp/terra/theiaprok-files/Mtb_NC_000962.3.fasta
Masking repetitive regions of the genome (e.g. PE/PPE genes) that are often misaligned
- snippy_core_bed = gs://theiagen-public-files/terra/theiaprok-files/Mtb_NC_000962.3.bed
Without masking recombination because TB can be considered non-recombinant
- use_gubbins = false
Using the core genome
- core_genome = true (as default)

Terra Task Name	Variable	Type	Description	Default Value	Terra Status
snippy_tree_wf	tree_name_updated	String	Internal component, do not modify. Used for replacing spaces with underscores_		Do not modify
snippy_tree_wf	reference_genome_file	File	Reference genome in FASTA or GENBANK format (must be the same reference used in Snippy_Variants workflow)		Required
snippy_tree_wf	samplenames	Array[String]	Samplenames for each input genome		Required
snippy_tree_wf	snippy_variants_outdir_tarball	Array[File]	Output from the Snippy_Variants workflow		Required
snippy_tree_wf	tree_name	String	String of your choice to prefix output files		Required
cg_reorder_matrix	cpu	Int	Number of CPUs to allocate to the task	2	Optional
cg_reorder_matrix	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
cg_reorder_matrix	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/mykrobe:0.12.1	Optional
cg_reorder_matrix	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional
cg_snp_dists	cpu	Int	Number of CPUs to allocate to the task	1	Optional
cg_snp_dists	disk_size	Int	Amount of storage (in GB) to allocate to the task	50	Optional
cg_snp_dists	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional
concatenate_variants	docker_image	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/theiagen/utility:1.1	Optional
gubbins	filter_percent	Int	Maximum % gaps to include a sample in gubbins analysis and downstream analyses	25	Optional
gubbins	iterations	Int	Maximum number of trees to iteratively build to remove recombination	5	Optional
gubbins	nuc_subst_model	String	Nucleotide substitution model to use with Gubbins: "JC", "K2P", "HKY", "GTR", "GTRGAMMA" or "GTRCAT" (see https://github.com/nickjcroucher/gubbins/blob/v3.3/docs/gubbins_manual.md#nucleotide-substitution-model-options)	GTRGAMMA	Optional
gubbins	tree_args	String	Quoted string of further arguments passed to tree building algorithm		Optional
gubbins	tree_builder	String	Application to use for Gubbins tree building algorithm: "raxml", "raxmlng", "iqtree", "iqtree-fast", "fasttree", "hybrid" (fasttree is used for the first tree, and raxml is used for later iterations), "rapidnj"	raxml	Optional
iqtree2	alrt	Int	Number of replicates to use for the SH-like approximate likelihood ratio test (Minimum recommended= 1000)	1000	Optional
shared_variants	cpu	Int	Number of CPUs to allocate to the task	1	Optional
shared_variants	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
shared_variants	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/theiagen/terra-tools:2023-03-16	Optional
shared_variants	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	8	Optional
snippy_tree_wf	call_shared_variants	Boolean	When true, workflow generates table that combines variants across all samples and a table showing variants shared across samples	TRUE	Optional
snippy_tree_wf	core_genome	Boolean	When true, workflow generates core genome phylogeny; when false, whole genome is used	TRUE	Optional
snippy_tree_wf	data_summary_column_names	String	A comma-separated list of the column names from the sample-level data table for generating a data summary (presence/absence .csv matrix)		Optional
snippy_tree_wf	data_summary_terra_project	String	The billing project for your current workspace. This can be found after the "#workspaces/" section in the workspace's URL		Optional
snippy_tree_wf	data_summary_terra_table	String	The name of the sample-level Terra data table that will be used for generating a data summary		Optional
snippy_tree_wf	data_summary_terra_workspace	String	The name of the Terra workspace you are in. This can be found at the top of the webpage, or in the URL after the billing project.		Optional
snippy_tree_wf	gubbins_cpu	Int	Number of CPUs to allocate to the task	4	Optional
snippy_tree_wf	gubbins_docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/biocontainers/gubbins:3.3--py310pl5321h8472f5a_0	Optional
snippy_tree_wf	gubbins_memory	Int	Amount of memory/RAM (in GB) to allocate to the task	32	Optional
snippy_tree_wf	gubbins_disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
snippy_tree_wf	iqtree2_bootstraps	String	Number of replicates for http://www.iqtree.org/doc/Tutorial#assessing-branch-supports-with-ultrafast-bootstrap-approximation (Minimum recommended= 1000)	1000	Optional
snippy_tree_wf	iqtree2_cpu	Int	Number of CPUs to allocate to the task	4	Optional
snippy_tree_wf	iqtree2_disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
snippy_tree_wf	iqtree2_docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/iqtree2:2.1.2	Optional
snippy_tree_wf	iqtree2_memory	Int	Amount of memory/RAM (in GB) to allocate to the task	32	Optional
snippy_tree_wf	iqtree2_model	String	Nucelotide substitution model to use when generating the final tree with IQTree2. By default, IQtree runs its ModelFinder algorithm to identify the model it thinks best fits your dataset		Optional
snippy_tree_wf	iqtree2_opts	String	Additional options to pass to IQTree2		Optional
snippy_tree_wf	midpoint_root_tree	Boolean	If true, midpoint root the final tree		Optional
snippy_tree_wf	phandango_coloring	Boolean	Boolean variable that tells the data summary task and the reorder matrix task to include a suffix that enables consistent coloring on Phandango; by default, this suffix is not added. To add this suffix set this variable to true.	FALSE	Optional
snippy_tree_wf	snippy_core_bed	File	Bed file with locations to be masked from the core genome alignment		Optional
snippy_tree_wf	snippy_core_cpu	Int	Number of CPUs to allocate to the task	8	Optional
snippy_tree_wf	snippy_core_disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
snippy_tree_wf	snippy_core_docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/snippy:4.6.0	Optional
snippy_tree_wf	snippy_core_memory	Int	Amount of memory/RAM (in GB) to allocate to the task	16	Optional
snippy_tree_wf	snp_dists_docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/snp-dists:0.8.2	Optional
snippy_tree_wf	snp_sites_cpus	Int	CPUs to allocate to SNP-sites	1	Optional
snippy_tree_wf	snp_sites_disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
snippy_tree_wf	snp_sites_docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/snp-sites:2.5.1	Optional
snippy_tree_wf	snp_sites_memory	Int	Amount of memory/RAM (in GB) to allocate to the task	4	Optional
snippy_tree_wf	use_gubbins	Boolean	When "true", workflow removed recombination with gubbins tasks; when "false", gubbins is not used	true	Optional
summarize_data	cpu	Int	Number of CPUs to allocate to the task	8	Optional
summarize_data	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
summarize_data	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/theiagen/terra-tools:2023-03-16	Optional
summarize_data	id_column_name	String	Name of the column in the input table that contains the sample IDs, if different from default		Optional
summarize_data	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	1	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
wg_reorder_matrix	cpu	Int	Number of CPUs to allocate to the task	2	Optional
wg_reorder_matrix	disk_size	Int	Amount of storage (in GB) to allocate to the task	100	Optional
wg_reorder_matrix	docker	String	The Docker container to use for the task	us-docker.pkg.dev/general-theiagen/staphb/mykrobe:0.12.1	Optional
wg_reorder_matrix	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional
wg_snp_dists	cpu	Int	Number of CPUs to allocate to the task	1	Optional
wg_snp_dists	disk_size	Int	Amount of storage (in GB) to allocate to the task	50	Optional
wg_snp_dists	memory	Int	Amount of memory/RAM (in GB) to allocate to the task	2	Optional

Workflow Tasks¶

Snippy

Snippy¶

Snippy is a pipeline for calling SNPs and INDELs in haploid genomes. Before running Snippy_Tree, you must run Snippy_Variants, another workflow that uses the Snippy tool to align reads against a reference genome for individual samples. In Snippy_Tree, the snippy tool is used again to generate a whole-genome multiple sequence alignment (fasta file) of reads from all the samples we'd like in our tree.

When generating the multiple sequence alignment, a bed file can be provided by users to mask certain areas of the genome in the alignment. This is particularly relevant for masking known repetitive regions in Mycobacterium tuberculosis genomes, or masking known regions containing phage sequences.

Why do I see snippy_core in Terra?

In Terra, this task is named "snippy_core" after the name of the command in the original Snippy tool. Despite the name, this command is NOT being used to make a core genome, but instead a multiple sequence alignment of the whole genome (without any sections masked using a bed file).

Snippy Technical Details

	Links
Task	task_snippy_core.wdl
Default software version	v4.6.0 (us-docker.pkg.dev/general-theiagen/staphb/snippy:4.6.0)
Software Source Code	Snippy on GitHub
Software Documentation	Snippy on GitHub

Gubbins (optional)

Gubbins (optional)¶

Optional

Gubbins is used when use_gubbins is set to true (default=true).

Genealogies Unbiased By recomBinations In Nucleotide Sequences (Gubbins) identifies and masks genomic regions that are predicted to have arisen via recombination. It works by iteratively identifying loci containing elevated densities of SNPs and constructing phylogenies based on the putative single nucleotide variants outside these regions (for more details, see here). By default, these phylogenies are constructed using RaxML and a GTR-GAMMA nucleotide substitution model, which will be the most suitable model for most bacterial phylogenetics, though this can be modified with the tree_builder and nuc_subst_model inputs.

Gubbins is the industry standard for masking recombination from bacterial genomes when building phylogenies, but limitations to recombination removal exist. Gubbins cannot distinguish recombination from high densities of SNPs that may result from assembly or alignment errors, mutational hotspots, or regions of the genome with relaxed selection. The tool is also intended only to find recombinant regions that are short relative to the length of the genome, so large regions of recombination may not be masked. These factors should be considered when interpreting resulting phylogenetic trees, but overwhelmingly Gubbins improves our ability to understand ancestral relationships between bacterial genomes.

There are few optional inputs for Gubbins that can be modified by the user:

iterations: Gubbins works by iteratively identifying loci containing elevated densities of SNPs, while constructing phylogenies based on the putative single nucleotide variants outside these regions. It may take many iterations for Gubbins to converge on an alignment that it considers free of recombination, especially for phylogenies that contain large numbers of genomes. By default, Gubbins is limited to 5 iterations though this may be increased by the user with the iterationsoptional input (incurring increased computing time and cost, and possibly requiring increased memory allocation).
nuc_subst_model, tree_builder and tree_args: When Gubbins constructs phylogenies, it can use a number of phylogenetic inference tools, each with different nucleotide substitution models and tree-building models. By default, the Snippy_Tree workflow uses a GTRGAMMA substitution model and RaxML for tree building (typically suitable for bacterial genomes), but these can be modified by the user depending on the genome sequences being used with the nuc_subst_model and tree_builder optional inputs, respectively. The nucleotide substitution models that are available depend on the tree building algorithm being used (see here). Additional options for generating the phylogenetic trees in Gubbins can be specified with the tree_args optional input, providing an input string that is consistent with the option formats of the Gubbins command.
filter_percent: By default, Gubbins removes genomes from the multiple sequence alignment if more than 25 % of the genome is represented by gaps. The percentage of gaps can be modified by the user using the filter_percent optional input.

Gubbins Technical Details

	Links
Task	task_gubbins.wdl
Software Source Code	Gubbins on GitHub
Software Documentation	Gubbins v3.3 manual
Original Publication(s)	Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins
Default software version	us-docker.pkg.dev/general-theiagen/biocontainers/gubbins:3.3--py310pl5321h8472f5a_0

SNP-sites (optional)

SNP-sites (optional)¶

Turn on SNP-Sites with core_genome

SNP-sites runs when the core_genome option is set to true.

SNP-sites is used to filter out invariant sites in the whole-genome alignment, thereby creating a core genome alignment for phylogenetic inference. The output is a fasta file containing the core genome of each sample only. If Gubbins has been used, this output fasta will not contain any sites that are predicted to have arisen via recombination.

SNP-sites technical details

	Links
Task	task_snp_sites.wdl
Default software version	2.5.1 (us-docker.pkg.dev/general-theiagen/biocontainers/snp-sites:2.5.1--hed695b0_0)
Software Source Code	SNP-sites on GitHub
Software Documentation	SNP-sites on GitHub
Original Publication(s)	SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments

IQTree2

IQTree2¶

IQTree2 is used to build the final phylogeny. It uses the alignment generated in the previous steps of the workflow. The contents of this alignment will depend on whether any sites were masked with recombination.

The phylogeny is generated using the maximum-likelihood method and a specified nucleotide substitution model. By default, the Snippy_Tree workflow will run Model Finder to determine the most appropriate nucleotide substitution model for your data, but you may specify the nucleotide substitution model yourself using the iqtree2_model optional input (see here for available models).

IQTree will perform assessments of the tree using the Shimodaira–Hasegawa approximate likelihood-ratio test (SH-aLRT test), and ultrafast bootstrapping with UFBoot2, a quicker but less biased alternative to standard bootstrapping. A clade should not typically be trusted if it has less than 80% support from the SH-aLRT test and less than 95% support with ultrafast bootstrapping.

Nucleotide substitution model

When core_genome= true, the default nucleotide substitution model is set to the General Time Reverside model with Gamma distribution (GTR+G).

When the user sets core_genome= false, the default nucleotide substitution model is set to the General Time Reversible model with invariant sites and Gamma distribution (GTR+I+G).

IQTree2 technical details

	Links
Task	task_iqtree2.wdl
Software Source Code	IQ-TREE on GitHub
Software Documentation	IQTree documentation for the latest version (not necessarily the version used in this workflow)
Original Publication(s)	IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era
Publication for the SH-alRT test	New Algorithms and Methods to Estimate Maximum-Likelihood Phylogenies: Assessing the Performance of PhyML 3.0
Publication for ultrafast bootstrapping integration to IQTree	Ultrafast Approximation for Phylogenetic Bootstrap; UFBoot2: Improving the Ultrafast Bootstrap Approximation
Publication for ModelFinder	ModelFinder: fast model selection for accurate phylogenetic estimates

SNP-dists

SNP-dists¶

SNP-dists computes pairwise SNP distances between genomes. It takes the same alignment of genomes used to generate your phylogenetic tree and produces a matrix of pairwise SNP distances between sequences. This means that if you generated pairwise core-genome phylogeny, the output will consist of pairwise core-genome SNP (cgSNP) distances. Otherwise, these will be whole-genome SNP distances. Regardless of whether core-genome or whole-genome SNPs, this SNP distance matrix will exclude all SNPs in masked regions (i.e. masked with a bed file or gubbins).

The SNP-distance output can be visualized using software such as Phandango to explore the relationships between the genomic sequences. The task adds a Phandango coloring tag (:c1) to the column names in the output matrix to ensure that all columns are colored with the same color scheme throughout.

SNP-dists Technical Details

	Links
Task	task_snp_dists.wdl
Default software version	0.8.2 (us-docker.pkg.dev/general-theiagen/staphb/snp-dists:0.8.2)
Software Source Code	SNP-dists on GitHub
Software Documentation	SNP-dists on GitHub
Original Publication(s)	Not known to be published

Data summary (optional)

Data Summary (optional)¶

If you fill out the data_summary_* and sample_names optional variables, you can use the optional summarize_data task. The task takes a comma-separated list of column names from the Terra data table, which should each contain a list of comma-separated items. For example, "amrfinderplus_virulence_genes,amrfinderplus_stress_genes" (with quotes, comma separated, no spaces) for these output columns from running TheiaProk. The task checks whether those comma-separated items are present in each row of the data table (sample), then creates a CSV file of these results. The CSV file indicates presence (TRUE) or absence (empty) for each item. By default, the task adds a Phandango coloring tag to group items from the same column, but you can turn this off by setting phandango_coloring to false.

Example output CSV

Sample_Name,aph(3')-IIa,blaCTX-M-65,blaOXA-193,tet(O)
sample1,TRUE,,TRUE,TRUE
sample2,,,FALSE,TRUE
sample3,,,FALSE,

Example use of Phandango coloring

Data summary produced using the phandango_coloring option, visualized alongside Newick tree at http://jameshadfield.github.io/phandango/#/main

Example phandango_coloring output

Data summary technical details

	Links
Task	task_summarize_data.wdl

Concatenate Variants (optional)

Concatenate Variants (optional)¶

The cat_variants task concatenates variant data from multiple samples into a single file concatenated_variants. It is very similar to the cat_files task, but also adds a column to the output file that indicates the sample associated with each row of data.

The concatenated_variants file will be in the following format:

samplename	CHROM	POS	TYPE	REF	ALT	EVIDENCE	FTYPE	STRAND	NT_POS	AA_POS	EFFECT	LOCUS_TAG	GENE
sample1	PEKT02000007	5224	snp	C	G	G:21 C:0
sample2	PEKT02000007	34112	snp	C	G	G:32 C:0	CDS	+	153/1620	51/539	missense_variant c.153C>G p.His51Gln	B9J08_002604	hypothetical protein
sample3	PEKT02000007	34487	snp	T	A	A:41 T:0	CDS	+	528/1620	176/539	missense_variant c.528T>A p.Asn176Lys	B9J08_002604	hypothetical protein

Technical Details

	Links
Task	/tasks/utilities/file_handling/task_cat_files.wdl
Software Source Code	task_cat_files.wdl

Shared Variants Task (Optional)

Shared Variants (optional)¶

The shared_variants task takes in the concatenated_variants output from the cat_variants task and reshapes the data so that variants are rows and samples are columns. For each variant, samples where the variant was detected are populated with a "1" and samples were either the variant was not detected or there was insufficient coverage to call variants are populated with a "0". The resulting table is available as the shared_variants_table output.

The shared_variants_table file will be in the following format:

CHROM	POS	TYPE	REF	ALT	FTYPE	STRAND	NT_POS	AA_POS	EFFECT	LOCUS_TAG	GENE	PRODUCT	sample1	sample2	sample3
PEKT02000007	2693938	snp	T	C	CDS	-	1008/3000	336/999	synonymous_variant c.1008A>G p.Lys336Lys	B9J08_003879	NA	chitin synthase 1	1	1	0
PEKT02000007	2529234	snp	G	C	CDS	+	282/336	94/111	missense_variant c.282G>C p.Lys94Asn	B9J08_003804	NA	cytochrome c	1	1	1
PEKT02000002	1043926	snp	A	G	CDS	-	542/1464	181/487	missense_variant c.542T>C p.Ile181Thr	B9J08_000976	NA	dihydrolipoyl dehydrogenase	1	1	0

Technical Details

	Links
Task	task_shared_variants.wdl
Software Source Code	task_shared_variants.wdl

Snippy_Variants QC Metrics Concatenation (optional)

Snippy_Variants QC Metric Concatenation (optional)¶

Optionally, the user can provide the snippy_variants_qc_metrics file produced by the Snippy_Variants workflow as input to the workflow to concatenate the reports for each sample in the tree. These per-sample QC metrics include the following columns:

samplename: The name of the sample.
reads_aligned_to_reference: The number of reads that aligned to the reference genome.
total_reads: The total number of reads in the sample.
percent_reads_aligned: The percentage of reads that aligned to the reference genome.
variants_total: The total number of variants detected between the sample and the reference genome.
percent_ref_coverage: The percentage of the reference genome covered by reads with a depth greater than or equal to the min_coverage threshold (default is 10).
#rname: Reference sequence name (e.g., chromosome or contig name).
startpos: Starting position of the reference sequence.
endpos: Ending position of the reference sequence.
numreads: Number of reads covering the reference sequence.
covbases: Number of bases with coverage.
coverage: Percentage of the reference sequence covered (depth ≥ 1).
meandepth: Mean depth of coverage over the reference sequence.
meanbaseq: Mean base quality over the reference sequence.
meanmapq: Mean mapping quality over the reference sequence.

The combined QC metrics file includes the same columns as above for all samples. Note that the last set of columns (#rname to meanmapq) may repeat for each chromosome or contig in the reference genome.

QC Metrics for Phylogenetic Analysis

These QC metrics provide valuable insights into the quality and coverage of your sequencing data relative to the reference genome. Monitoring these metrics can help identify samples with low coverage, poor alignment, or potential issues that may affect downstream analyses, and we recommend examining them before proceeding with phylogenetic analysis if performing Snippy_Variants and Snippy_Tree separately.

Snippy Variants Technical Details

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

Outputs¶

Variable	Type	Description
snippy_cg_snp_matrix	File	CSV file of core genome pairwise SNP distances between samples, calculated from the final alignment
snippy_concatenated_variants	File	Concatenated snippy_results file across all samples in the set
snippy_combined_qc_metrics	File	Combined QC metrics file containing concatenated QC metrics from all samples.
snippy_filtered_metadata	File	TSV recording the columns of the Terra data table that were used in the summarize_data task
snippy_final_alignment	File	Final alignment (FASTA file) used to generate the tree (either after snippy alignment, gubbins recombination removal, and/or core site selection with SNP-sites)
snippy_final_tree	File	Newick tree produced from the final alignment. Depending on user input for core_genome, the tree could be a core genome tree (default when core_genome is true) or whole genome tree (if core_genome is false)
snippy_gubbins_branch_stats	File	CSV file showing https://github.com/nickjcroucher/gubbins/blob/master/docs/gubbins_manual.md#output-statistics for each branch of the tree
snippy_gubbins_docker	String	Docker file used for running Gubbins
snippy_gubbins_recombination_gff	File	Recombination statistics in GFF format; these can be viewed in Phandango against the phylogenetic tree
snippy_gubbins_version	String	Gubbins version used
snippy_iqtree2_docker	String	Docker file used for running IQTree2
snippy_iqtree2_model_used	String	Nucleotide substitution model used by IQTree2
snippy_iqtree2_version	String	IQTree2 version used
snippy_msa_snps_summary	File	TXT file containing summary statistics for each alignment of each input genome against the reference. This indicates how good the alignment is. Pay particular attention to # unaligned sites, and heterogeneous positions.
snippy_ref	File	Reference genome (FASTA or GenBank file) used for generating phylogeny
snippy_shared_snp_table	File	Table illustrating variants shared among samples
snippy_snp_dists_docker	String	Docker file used for running SNP-dists
snippy_snp_dists_version	String	SNP-dists version used
snippy_snp_sites_docker	String	Docker file used for running SNP-sites
snippy_snp_sites_version	String	SNP-sites version used
snippy_summarized_data	File	CSV presence/absence matrix generated by the summarize_data task from the list of columns provided; formatted for Phandango if phandango_coloring input is true
snippy_tree_analysis_date	String	Date of workflow run
snippy_tree_snippy_docker	String	Docker file used for running Snippy
snippy_tree_snippy_version	String	Snippy version used
snippy_tree_version	String	Version of Snippy_Tree workflow
snippy_wg_snp_matrix	File	CSV file of whole genome pairwise SNP distances between samples, calculated from the final alignment

References¶

Gubbins: Croucher, Nicholas J., Andrew J. Page, Thomas R. Connor, Aidan J. Delaney, Jacqueline A. Keane, Stephen D. Bentley, Julian Parkhill, and Simon R. Harris. 2015. "Rapid Phylogenetic Analysis of Large Samples of Recombinant Bacterial Whole Genome Sequences Using Gubbins." Nucleic Acids Research 43 (3): e15.

SNP-sites: Page, Andrew J., Ben Taylor, Aidan J. Delaney, Jorge Soares, Torsten Seemann, Jacqueline A. Keane, and Simon R. Harris. 2016. "SNP-Sites: Rapid Efficient Extraction of SNPs from Multi-FASTA Alignments." Microbial Genomics 2 (4): e000056.

IQTree: Nguyen, Lam-Tung, Heiko A. Schmidt, Arndt von Haeseler, and Bui Quang Minh. 2015. "IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies." Molecular Biology and Evolution 32 (1): 268–74.