Full Guide

Bactopia is a complete pipeline for the analysis of bacterial genomes, which includes more than 150 bioinformatics tools. In this section, each step of the pipeline will be described in detail. This includes the input data, output data, and the parameters for each step.

Looking at the workflow overview below, it might not look like much is happening, but I can assure you that a lot is going on. The workflow is broken down into 8 steps, which are:

1. Gather - Collect all the data in one place
2. QC - Quality control of the data
3. Assembler - Assemble the reads into contigs
4. Annotator - Annotate the contigs
5. Sketcher - Create a sketch of the contigs, and query databases
6. Sequence Typing - Determine the sequence type of the contigs
7. Antibiotic Resistance - Determine the antibiotic resistance of the contigs and proteins
8. Merlin - Automatically run species-specific tools based on distance

This guide is meant to be extensive, so it will be very detailed. If you are looking for a guide to get started quickly, please check out the Beginner's Guide.

Otherwise, let's get started!

Step 1 - Gather

The main purpose of the gather step is to get all the samples into a single place. This includes downloading samples from ENA/SRA or NCBI Assembly. The tools used are:

Tool	Description
art	For simulating error-free reads for an input assembly
fastq-dl	Downloading FASTQ files from ENA/SRA
ncbi-genome-download	Downloading FASTA files from NCBI Assembly

This gather step also does basic QC checks to help prevent downstream failures.

Outputs

Merged Results

Below are results that are concatenated into a single file.

Filename	Description
meta.tsv	A tab-delimited file with bactopia metadata for all samples

gather

Below is a description of the per-sample results from the gather subworkflow.

Filename	Description
-meta.tsv	A tab-delimited file with bactopia metadata for each sample

Failed Quality Checks

Built into Bactopia are few basic quality checks to help prevent downstream failures. If a sample fails one of these checks, it will be excluded from further analysis. By excluding these samples, complete pipeline failures are prevented.

Filename	Description
-gzip-error.txt	Sample failed Gzip checks and excluded from further analysis
-low-basepair-proportion-error.txt	Sample failed basepair proportion checks and excluded from further analysis
-low-read-count-error.txt	Sample failed read count checks and excluded from further analysis
-low-sequence-depth-error.txt	Sample failed sequenced basepair checks and excluded from further analysis

Poor samples are excluded to prevent downstream failures

Samples that fail any of the QC checks will be excluded from further analysis. Those samples will generate a *-error.txt file with the error message. Excluding these samples prevents downstream failures that cause the whole workflow to fail.

Example Error: Input FASTQ(s) failed Gzip checks

If input FASTQ(s) fail to pass Gzip test, the sample will be excluded from further analysis.

Example Text from <SAMPLE_NAME>-gzip-error.txt
<SAMPLE_NAME> FASTQs failed Gzip tests. Please check the input FASTQs. Further analysis is discontinued.

Example Error: Input FASTQs have disproportionate number of reads

If input FASTQ(s) for a sample have disproportionately different number of reads between the two pairs, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_proportion parameter.

Example Text from <SAMPLE_NAME>-low-basepair-proportion-error.txt
<SAMPLE_NAME> FASTQs failed to meet the minimum shared basepairs (X``). They shared Ybasepairs, with R1 havingAbp and R2 havingB` bp. Further analysis is discontinued.

Example Error: Input FASTQ(s) has too few reads

If input FASTQ(s) for a sample have less than the minimum required reads, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_reads parameter.

Example Text from <SAMPLE_NAME>-low-read-count-error.txt
<SAMPLE_NAME> FASTQ(s) contain X total reads. This does not exceed the required minimum Y read count. Further analysis is discontinued.

Example Error: Input FASTQ(s) has too little sequenced basepairs

If input FASTQ(s) for a sample fails to meet the minimum number of sequenced basepairs, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_basepairs parameter.

Example Text from <SAMPLE_NAME>-low-sequence-depth-error.txt
<SAMPLE_NAME> FASTQ(s) contain X total basepairs. This does not exceed the required minimum Y bp. Further analysis is discontinued.

Parameters

Required

The following parameters are how you will provide either local or remote samples to be processed by Bactopia.

Parameter	Description
--samples	A FOFN (via bactopia prepare) with sample names and paths to FASTQ/FASTAs to process Type: string
--r1	First set of compressed (gzip) Illumina paired-end FASTQ reads (requires --r2 and --sample) Type: string
--r2	Second set of compressed (gzip) Illumina paired-end FASTQ reads (requires --r1 and --sample) Type: string
--se	Compressed (gzip) Illumina single-end FASTQ reads (requires --sample) Type: string
--ont	Compressed (gzip) Oxford Nanopore FASTQ reads (requires --sample) Type: string
--hybrid	Create hybrid assembly using Unicycler. (requires --r1, --r2, --ont and --sample) Type: boolean
--short_polish	Create hybrid assembly from long-read assembly and short read polishing. (requires --r1, --r2, --ont and --sample) Type: boolean
--sample	Sample name to use for the input sequences Type: string
--accessions	A file containing ENA/SRA Experiment accessions or NCBI Assembly accessions to processed Type: string
--accession	Sample name to use for the input sequences Type: string
--assembly	A assembled genome in compressed FASTA format. (requires --sample) Type: string
--check_samples	Validate the input FOFN provided by --samples Type: boolean

Dataset

Define where the pipeline should find input data and save output data.

Parameter	Description
--species	Name of species for species-specific dataset to use Type: string
--ask_merlin	Ask Merlin to execute species specific Bactopia tools based on Mash distances Type: boolean
--coverage	Reduce samples to a given coverage, requires a genome size Type: integer, Default: 100
--genome_size	Expected genome size (bp) for all samples, required for read error correction and read subsampling Type: string, Default: 0
--use_bakta	Use Bakta for annotation, instead of Prokka Type: boolean

Citations

If you use Bactopia and gather results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• ART
  Huang W, Li L, Myers JR, Marth GT ART: a next-generation sequencing read simulator. Bioinformatics 28, 593–594 (2012)

• fastq-dl
  Petit III RA fastq-dl: Download FASTQ files from SRA or ENA repositories. (GitHub)

• fastq-scan
  Petit III RA fastq-scan: generate summary statistics of input FASTQ sequences. (GitHub)

• ncbi-genome-download
  Blin K ncbi-genome-download: Scripts to download genomes from the NCBI FTP servers (GitHub)

• Pigz
  Adler M. pigz: A parallel implementation of gzip for modern multi-processor, multi-core machines. Jet Propulsion Laboratory (2015)

Step 2 - QC

The qc module uses a variety of tools to perform quality control on Illumina and Oxford Nanopore reads. The tools used are:

Tool	Technology	Description
bbtools	Illumina	A suite of tools for manipulating reads
fastp	Illumina	A tool designed to provide fast all-in-one preprocessing for FastQ files
fastqc	Illumina	A quality control tool for high throughput sequence data
fastq_scan	Nanopore	A tool for quickly scanning FASTQ files
lighter	Illumina	A tool for correcting sequencing errors in Illumina reads
NanoPlot	Nanopore	A tool for plotting long read sequencing data
nanoq	Nanopore	A tool for calculating quality metrics for Oxford Nanopore reads
porechop	Nanopore	A tool for removing adapters from Oxford Nanopore reads
rasusa	Nanopore	Randomly subsample sequencing reads to a specified coverage

Similar to the gather step, the qc step will also stop samples that fail to meet basic QC checks from continuing downstream.

Outputs

Quality Control

Below is a description of the per-sample results from qc subworkflow.

Filename	Description
<SAMPLE_NAME>.fastq.gz	A gzipped FASTQ file containing the cleaned Illumina single-end, or Oxford Nanopore reads
<SAMPLE_NAME>_R{1|2}.fastq.gz	A gzipped FASTQ file containing the cleaned Illumina paired-end reads
<SAMPLE_NAME>-{final|original}.json	A JSON file containing the QC results generated by fastq-scan
<SAMPLE_NAME>-{final|original}_fastqc.html	(Illumina Only) A HTML report of the QC results generated by fastqc
<SAMPLE_NAME>-{final|original}_fastqc.zip	(Illumina Only) A zip file containing the complete set of fastqc results
<SAMPLE_NAME>-{final|original}_fastp.json	(Illumina Only) A JSON file containing the QC results generated by fastp
<SAMPLE_NAME>-{final|original}_fastp.html	(Illumina Only) A HTML report of the QC results generated by fastp
<SAMPLE_NAME>-{final|original}_NanoPlot-report.html	(ONT Only) A HTML report of the QC results generated by NanoPlot
<SAMPLE_NAME>-{final|original}_NanoPlot.tar.gz	(ONT Only) A tarball containing the complete set of NanoPlot results

Failed Quality Checks

Built into Bactopia are few basic quality checks to help prevent downstream failures. If a sample fails one of these checks, it will be excluded from further analysis. By excluding these samples, complete pipeline failures are prevented.

Filename	Description
.error-fastq.gz	A gzipped FASTQ file of Illumina Single-End or Oxford Nanopore reads that failed QC
_R{1|2}.error-fastq.gz	A gzipped FASTQ file of Illumina Single-End or Oxford Nanopore reads that failed QC
-low-read-count-error.txt	Sample failed read count checks and excluded from further analysis
-low-sequence-coverage-error.txt	Sample failed sequenced coverage checks and excluded from further analysis
-low-sequence-depth-error.txt	Sample failed sequenced basepair checks and excluded from further analysis

Poor samples are excluded to prevent downstream failures

Samples that fail any of the QC checks will be excluded from further analysis. Those samples will generate a *-error.txt file with the error message. Excluding these samples prevents downstream failures that cause the whole workflow to fail.

Example Error: After QC, too few reads remain

If after cleaning reads, a sample has less than the minimum required reads, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_reads parameter.

Example Text from <SAMPLE_NAME>-low-read-count-error.txt
<SAMPLE_NAME> FASTQ(s) contain X total reads. This does not exceed the required minimum Y read count. Further analysis is discontinued.

Example Error: After QC, too little sequence coverage remains

If after cleaning reads, a sample has failed to meet the minimum sequence coverage required, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_coverage parameter.

Note: This check is only performed when a genome size is available.

Example Text from <SAMPLE_NAME>-low-sequence-coverage-error.txt
After QC, <SAMPLE_NAME> FASTQ(s) contain X total basepairs. This does not exceed the required minimum Y bp (Zx coverage). Further analysis is discontinued.

Example Error: After QC, too little sequenced basepairs remain

If after cleaning reads, a sample has failed to meet the minimum number of sequenced basepairs, the sample will be excluded from further analysis. You can adjust this minimum read count using the --min_basepairs parameter.

Example Text from <SAMPLE_NAME>-low-sequence-depth-error.txt
<SAMPLE_NAME> FASTQ(s) contain X total basepairs. This does not exceed the required minimum Y bp. Further analysis is discontinued.

QC Parameters

Parameter	Description
--use_bbmap	Illumina reads will be QC'd using BBMap Type: boolean
--use_porechop	Use Porechop to remove adapters from ONT reads Type: boolean
--skip_qc	The QC step will be skipped and it will be assumed the inputs sequences have already been QCed. Type: boolean
--skip_qc_plots	QC Plot creation by FastQC or Nanoplot will be skipped Type: boolean
--skip_error_correction	FLASH error correction of reads will be skipped. Type: boolean
--adapters	A FASTA file containing adapters to remove Type: string, Default: /home/robert_petit/bactopia/data/EMPTY_ADAPTERS
--adapter_k	Kmer length used for finding adapters. Type: integer, Default: 23
--phix	phiX174 reference genome to remove Type: string, Default: /home/robert_petit/bactopia/data/EMPTY_PHIX
--phix_k	Kmer length used for finding phiX174. Type: integer, Default: 31
--ktrim	Trim reads to remove bases matching reference kmers Type: string, Default: r
--mink	Look for shorter kmers at read tips down to this length, when k-trimming or masking. Type: integer, Default: 11
--hdist	Maximum Hamming distance for ref kmers (subs only) Type: integer, Default: 1
--tpe	When kmer right-trimming, trim both reads to the minimum length of either Type: string, Default: t
--tbo	Trim adapters based on where paired reads overlap Type: string, Default: t
--qtrim	Trim read ends to remove bases with quality below trimq. Type: string, Default: rl
--trimq	Regions with average quality BELOW this will be trimmed if qtrim is set to something other than f Type: integer, Default: 6
--maq	Reads with average quality (after trimming) below this will be discarded Type: integer, Default: 10
--minlength	Reads shorter than this after trimming will be discarded Type: integer, Default: 35
--ftm	If positive, right-trim length to be equal to zero, modulo this number Type: integer, Default: 5
--tossjunk	Discard reads with invalid characters as bases Type: string, Default: t
--ain	When detecting pair names, allow identical names Type: string, Default: f
--qout	PHRED offset to use for output FASTQs Type: string, Default: 33
--maxcor	Max number of corrections within a 20bp window Type: integer, Default: 1
--sampleseed	Set to a positive number to use as the random number generator seed for sampling Type: integer, Default: 42
--ont_minlength	ONT Reads shorter than this will be discarded Type: integer, Default: 1000
--ont_minqual	Minimum average read quality filter of ONT reads Type: integer
--porechop_opts	Extra Porechop options in quotes Type: string
--nanoplot_opts	Extra NanoPlot options in quotes Type: string
--bbduk_opts	Extra BBDuk options in quotes Type: string
--fastp_opts	Extra fastp options in quotes Type: string

Citations

If you use Bactopia and qc results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• BBTools
  Bushnell B BBMap short read aligner, and other bioinformatic tools. (Link)

• fastp
  Chen S, Zhou Y, Chen Y, and Gu J fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics, 34(17), i884–i890. (2018)

• fastq-scan
  Petit III RA fastq-scan: generate summary statistics of input FASTQ sequences. (GitHub)

• FastQC
  Andrews S FastQC: a quality control tool for high throughput sequence data. (WebLink)

• Lighter
  Song L, Florea L, Langmead B Lighter: Fast and Memory-efficient Sequencing Error Correction without Counting. Genome Biol. 15(11):509 (2014)

• NanoPlot
  De Coster W, D’Hert S, Schultz DT, Cruts M, Van Broeckhoven C NanoPack: visualizing and processing long-read sequencing data Bioinformatics Volume 34, Issue 15 (2018)

• Nanoq
  Steinig E Nanoq: Minimal but speedy quality control for nanopore reads in Rust (GitHub)

• Pigz
  Adler M. pigz: A parallel implementation of gzip for modern multi-processor, multi-core machines. Jet Propulsion Laboratory (2015)

• Porechop
  Wick RR, Judd LM, Gorrie CL, Holt KE. Completing bacterial genome assemblies with multiplex MinION sequencing. Microb Genom. 3(10):e000132 (2017)

• Rasusa
  Hall MB Rasusa: Randomly subsample sequencing reads to a specified coverage. (2019).

Step 3 - Assembler

The assembler module uses a variety of assembly tools to create an assembly of Illumina and Oxford Nanopore reads. The tools used are:

Tool	Description
Dragonflye	Assembly of Oxford Nanopore reads, as well as hybrid assembly with short-read polishing
Shovill	Assembly of Illumina paired-end reads
Shovill-SE	Assembly of Illumina single-end reads
Unicycler	Hybrid assembly, using short-reads first then long-reads

Summary statistics for each assembly are generated using assembly-scan.

Outputs

Merged Results

Below are results that are concatenated into a single file.

Filename	Description
assembly-scan.tsv	Assembly statistics for all samples

Dragonflye

Below is a description of the per-sample results for Oxford Nanopore reads using Dragonflye.

Filename	Description
<SAMPLE_NAME>.fna.gz	The final assembly produced by Dragonflye
<SAMPLE_NAME>.tsv	A tab-delimited file containing assembly statistics
flye-info.txt	A log file containing information about the Flye assembly
{flye|miniasm|raven}-unpolished.fasta.gz	Raw unprocessed assembly produced by the used assembler
{flye|miniasm|raven}-unpolished.gfa.gz	Raw unprocessed assembly graph produced by the used assembler

Shovill

Below is a description of the per-sample results for Illumina reads using Shovill or Shovill-SE.

Filename	Description
<SAMPLE_NAME>.fna.gz	The final assembly produced by Dragonflye
<SAMPLE_NAME>.tsv	A tab-delimited file containing assembly statistics
flash.hist	(Paired-End Only) Numeric histogram of merged read lengths.
flash.histogram	(Paired-End Only) Visual histogram of merged read lengths
{megahit|spades|velvet}-unpolished.gfa.gz	Raw unprocessed assembly graph produced by the used assembler
shovill.corrections	List of post-assembly corrections made by Shovill

Hybrid Assembly (Unicycler)

Below is a description of the per-sample results for a hybrid assembly using Unicycler (--hybrid). When using Unicycler, the short-reads are assembled first, then the long-reads are used to polish the assembly.

Filename	Description
<SAMPLE_NAME>.fna.gz	The final assembly produced by Dragonflye
<SAMPLE_NAME>.tsv	A tab-delimited file containing assembly statistics
unicycler-unpolished.fasta.gz	Raw unprocessed assembly produced by Unicycler
unicycler-unpolished.fasta.gz	Raw unprocessed assembly graph produced by Unicycler

Hybrid Assembly (Short Read Polishing)

Below is a description of the per-sample results for a hybrid assembly using Dragonflye (--short_polish). When using Dragonflye, the long-reads are assembled first, then the short-reads are used to polish the assembly.

tip

Prefer --short_polish over --hybrid with recent ONT sequencing

Using Unicycler (--hybrid) to create a hybrid assembly works great when you have low-coverage noisy long-reads. However, if you are using recent ONT sequencing, you likely have high-coverage and using the --short_polish method is going to yeild better results (and be faster!) than --hybrid.

Filename	Description
<SAMPLE_NAME>.fna.gz	The final assembly produced by Dragonflye
<SAMPLE_NAME>.tsv	A tab-delimited file containing assembly statistics
flye-info.txt	A log file containing information about the Flye assembly
{flye|miniasm|raven}-unpolished.fasta.gz	Raw unprocessed assembly produced by the used assembler
{flye|miniasm|raven}-unpolished.gfa.gz	Raw unprocessed assembly graph produced by the used assembler

Failed Quality Checks

Built into Bactopia are few basic quality checks to help prevent downstream failures. If a sample fails one of these checks, it will be excluded from further analysis. By excluding these samples, complete pipeline failures are prevented.

Filename	Description
-assembly-error.txt	Sample failed read count checks and excluded from further analysis

Poor samples are excluded to prevent downstream failures

Samples that fail any of the QC checks will be excluded from further analysis. Those samples will generate a *-error.txt file with the error message. Excluding these samples prevents downstream failures that cause the whole workflow to fail.

Example Error: Assembled Successfully, but 0 Contigs

If a sample assembles successfully, but 0 contigs are formed, the sample will be excluded from further analysis.

Example Text from <SAMPLE_NAME>-assembly-error.txt
<SAMPLE_NAME> assembled successfully, but 0 contigs were formed. Please investigate <SAMPLE_NAME> to determine a cause (e.g. metagenomic, contaminants, etc...) for this outcome. Further assembly-based analysis of <SAMPLE_NAME> will be discontinued.

Example Error: Assembled successfully, but poor assembly size

If you sample assembles successfully, but the assembly size is less than the minimum allowed genome size, the sample will be excluded from further analysis. You can adjust this minimum size using the --min_genome_size parameter.

Example Text from <SAMPLE_NAME>-assembly-error.txt
<SAMPLE_NAME> assembled size (000 bp) is less than the minimum allowed genome size (000 bp). If this is unexpected, please investigate <SAMPLE_NAME> to determine a cause (e.g. metagenomic, contaminants, etc...) for the poor assembly. Otherwise, adjust the --min_genome_size parameter to fit your need. Further assembly based analysis of <SAMPLE_NAME> will be discontinued.

Assembler Parameters

Parameter	Description
--shovill_assembler	Assembler to be used by Shovill Type: string, Default: skesa
--dragonflye_assembler	Assembler to be used by Dragonflye Type: string, Default: flye
--use_unicycler	Use unicycler for paired end assembly Type: boolean
--min_contig_len	Minimum contig length <0=AUTO> Type: integer, Default: 500
--min_contig_cov	Minimum contig coverage <0=AUTO> Type: integer, Default: 2
--contig_namefmt	Format of contig FASTA IDs in 'printf' style Type: string
--shovill_opts	Extra assembler options in quotes for Shovill Type: string
--shovill_kmers	K-mers to use <blank=AUTO> Type: string
--dragonflye_opts	Extra assembler options in quotes for Dragonflye Type: string
--trim	Enable adaptor trimming Type: boolean
--no_stitch	Disable read stitching for paired-end reads Type: boolean
--no_corr	Disable post-assembly correction Type: boolean
--unicycler_mode	Bridging mode used by Unicycler Type: string, Default: normal
--min_polish_size	Contigs shorter than this value (bp) will not be polished using Pilon Type: integer, Default: 10000
--min_component_size	Graph dead ends smaller than this size (bp) will be removed from the final graph Type: integer, Default: 1000
--min_dead_end_size	Graph dead ends smaller than this size (bp) will be removed from the final graph Type: integer, Default: 1000
--nanohq	For Flye, use '--nano-hq' instead of --nano-raw Type: boolean
--medaka_model	The model to use for Medaka polishing Type: string
--medaka_rounds	The number of Medaka polishing rounds to conduct Type: integer
--racon_rounds	The number of Racon polishing rounds to conduct Type: integer, Default: 1
--no_polish	Skip the assembly polishing step Type: boolean
--no_miniasm	Skip miniasm+Racon bridging Type: boolean
--no_rotate	Do not rotate completed replicons to start at a standard gene Type: boolean
--reassemble	If reads were simulated, they will be used to create a new assembly. Type: boolean
--polypolish_rounds	Number of polishing rounds to conduct with Polypolish for short read polishing Type: integer, Default: 1
--pilon_rounds	Number of polishing rounds to conduct with Pilon for short read polishing Type: integer

Citations

If you use Bactopia and assembler results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• any2fasta
  Seemann T any2fasta: Convert various sequence formats to FASTA (GitHub)

• assembly-scan
  Petit III RA assembly-scan: generate basic stats for an assembly (GitHub)

• BWA
  Li H Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv [q-bio.GN] (2013)

• csvtk
  Shen, W csvtk: A cross-platform, efficient and practical CSV/TSV toolkit in Golang. (GitHub)

• Dragonflye
  Petit III RA Dragonflye: Assemble bacterial isolate genomes from Nanopore reads. (GitHub)

• FLASH
  Magoč T, Salzberg SL FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27.21 2957-2963 (2011)

• Flye
  Kolmogorov M, Yuan J, Lin Y, Pevzner P Assembly of Long Error-Prone Reads Using Repeat Graphs Nature Biotechnology (2019)

• Medaka
  ONT Research Medaka: Sequence correction provided by ONT Research (GitHub)

• MEGAHIT
  Li D, Liu C-M, Luo R, Sadakane K, Lam T-W MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31.10 1674-1676 (2015)

• Miniasm
  Li H Miniasm: Ultrafast de novo assembly for long noisy reads (GitHub)

• Minimap2
  Li H Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 34:3094-3100 (2018)

• Nanoq
  Steinig E Nanoq: Minimal but speedy quality control for nanopore reads in Rust (GitHub)

• Pigz
  Adler M. pigz: A parallel implementation of gzip for modern multi-processor, multi-core machines. Jet Propulsion Laboratory (2015)

• Pilon
  Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, Cuomo CA, Zeng Q, Wortman J, Young SK, Earl AM Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PloS one 9.11 e112963 (2014)

• Racon
  Vaser R, Sović I, Nagarajan N, Šikić M Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res 27, 737–746 (2017)

• Rasusa
  Hall MB Rasusa: Randomly subsample sequencing reads to a specified coverage. (2019).

• Raven
  Vaser R, Šikić M Time- and memory-efficient genome assembly with Raven. Nat Comput Sci 1, 332–336 (2021)

• samclip
  Seemann T Samclip: Filter SAM file for soft and hard clipped alignments (GitHub)

• Samtools
  Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

• Shovill
  Seemann T Shovill: De novo assembly pipeline for Illumina paired reads (GitHub)

• Shovill-SE
  Petit III RA Shovill-SE: A fork of Shovill that includes support for single end reads. (GitHub)

• SKESA
  Souvorov A, Agarwala R, Lipman DJ SKESA: strategic k-mer extension for scrupulous assemblies. Genome Biology 19:153 (2018)

• SPAdes
  Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. Journal of computational biology 19.5 455-477 (2012)

• Unicycler
  Wick RR, Judd LM, Gorrie CL, Holt KE Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput. Biol. 13, e1005595 (2017)

• Velvet
  Zerbino DR, Birney E Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome research 18.5 821-829 (2008)

Step 4 - Annotator

Outputs

Prokka

Below is a description of the per-sample results from Prokka.

Filename	Description
.blastdb.tar.gz	A gzipped tar archive of BLAST+ database of the contigs, genes, and proteins
.faa.gz	Protein FASTA file of the translated CDS sequences.
.ffn.gz	Nucleotide FASTA file of all the prediction transcripts (CDS, rRNA, tRNA, tmRNA, misc_RNA)
.fna.gz	Nucleotide FASTA file of the input contig sequences.
.gbk.gz	This is a standard GenBank file derived from the master .gff. If the input to prokka was a multi-FASTA, then this will be a multi-GenBank, with one record for each sequence.
.gff.gz	This is the master annotation in GFF3 format, containing both sequences and annotations. It can be viewed directly in Artemis or IGV.
.sqn.gz	An ASN1 format "Sequin" file for submission to GenBank. It needs to be edited to set the correct taxonomy, authors, related publication etc.
.tbl.gz	Feature Table file, used by "tbl2asn" to create the .sqn file.
.tsv	Tab-separated file of all features (locus_tag,ftype,len_bp,gene,EC_number,COG,product)
.txt	Statistics relating to the annotated features found.

Bakta

Below is a description of the per-sample results from Bakta.

Filename	Description
.blastdb.tar.gz	A gzipped tar archive of BLAST+ database of the contigs, genes, and proteins
.embl.gz	Annotations & sequences in (multi) EMBL format
.faa.gz	CDS/sORF amino acid sequences as FASTA
.ffn.gz	Feature nucleotide sequences as FASTA
.fna.gz	Replicon/contig DNA sequences as FASTA
.gbff.gz	Annotations & sequences in (multi) GenBank format
.gff3.gz	Annotations & sequences in GFF3 format
.hypotheticals.faa.gz	Hypothetical protein CDS amino acid sequences as FASTA
.hypotheticals.tsv	Further information on hypothetical protein CDS as simple human readable tab separated values
.tsv	Annotations as simple human readable tab separated values
.txt	Broad summary of Bakta annotations

Parameters

Prokka

Parameter	Description
--proteins	FASTA file of trusted proteins to first annotate from Type: string
--prodigal_tf	Training file to use for Prodigal Type: string
--compliant	Force Genbank/ENA/DDJB compliance Type: boolean
--centre	Sequencing centre ID Type: string, Default: Bactopia
--prokka_coverage	Minimum coverage on query protein Type: integer, Default: 80
--prokka_evalue	Similarity e-value cut-off Type: string, Default: 1e-09
--prokka_opts	Extra Prokka options in quotes. Type: string

Bakta Download

Parameter	Description
--bakta_db	Tarball or path to the Bakta database Type: string
--bakta_db_type	Which Bakta DB to download 'full' (~30GB) or 'light' (~2GB) Type: string, Default: full
--bakta_save_as_tarball	Save the Bakta database as a tarball Type: boolean
--download_bakta	Download the Bakta database to the path given by --bakta_db Type: boolean

Bakta

Parameter	Description
--proteins	FASTA file of trusted proteins to first annotate from Type: string
--prodigal_tf	Training file to use for Prodigal Type: string
--replicons	Replicon information table (tsv/csv) Type: string
--min_contig_length	Minimum contig size to annotate Type: integer, Default: 1
--keep_contig_headers	Keep original contig headers Type: boolean
--compliant	Force Genbank/ENA/DDJB compliance Type: boolean
--skip_trna	Skip tRNA detection & annotation Type: boolean
--skip_tmrna	Skip tmRNA detection & annotation Type: boolean
--skip_rrna	Skip rRNA detection & annotation Type: boolean
--skip_ncrna	Skip ncRNA detection & annotation Type: boolean
--skip_ncrna_region	Skip ncRNA region detection & annotation Type: boolean
--skip_crispr	Skip CRISPR array detection & annotation Type: boolean
--skip_cds	Skip CDS detection & annotation Type: boolean
--skip_sorf	Skip sORF detection & annotation Type: boolean
--skip_gap	Skip gap detection & annotation Type: boolean
--skip_ori	Skip oriC/oriT detection & annotation Type: boolean
--bakta_opts	Extra Backa options in quotes. Example: '--gram +' Type: string

Citations

If you use Bactopia and annotator results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• Prokka
  Seemann T Prokka: rapid prokaryotic genome annotation Bioinformatics 30, 2068–2069 (2014)

• Bakta
  Schwengers O, Jelonek L, Dieckmann MA, Beyvers S, Blom J, Goesmann A Bakta - rapid and standardized annotation of bacterial genomes via alignment-free sequence identification. Microbial Genomics 7(11) (2021)

Step 5 - Sketcher

The sketcher module uses Mash and Sourmash to create sketches and query RefSeq and GTDB.

Outputs

sketcher

Below is a description of the per-sample results from the sketcher subworkflow.

Filename	Description
<SAMPLE_NAME>-k{21|31}.msh	A Mash sketch of the input assembly for k=21 and k=31
<SAMPLE_NAME>-mash-refseq88-k21.txt	The results of querying the Mash sketch against RefSeq88
<SAMPLE_NAME>-sourmash-gtdb-rs207-k31.txt	The results of querying the Sourmash sketch against GTDB-rs207
<SAMPLE_NAME>.sig	A Sourmash sketch of the input assembly for k=21, k=31, and k=51

Sketcher Parameters

Parameter	Description
--sketch_size	Sketch size. Each sketch will have at most this many non-redundant min-hashes. Type: integer, Default: 10000
--sourmash_scale	Choose number of hashes as 1 in FRACTION of input k-mers Type: integer, Default: 10000
--no_winner_take_all	Disable winner-takes-all strategy for identity estimates Type: boolean
--screen_i	Minimum identity to report. Type: number, Default: 0.8

Citations

If you use Bactopia and sketcher results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• Genome Taxonomy Database
  Parks DH, Chuvochina M, Rinke C, Mussig AJ, Chaumeil P-A, Hugenholtz P GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy Nucleic Acids Research gkab776 (2021)

• Mash
  Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17, 132 (2016)

• Mash
  Ondov BD, Starrett GJ, Sappington A, Kostic A, Koren S, Buck CB, Phillippy AM Mash Screen: high-throughput sequence containment estimation for genome discovery Genome Biol 20, 232 (2019)

• NCBI RefSeq Database
  O'Leary NA, Wright MW, Brister JR, Ciufo S, Haddad D, McVeigh R, Rajput B, Robbertse B, Smith-White B, Ako-Adjei D, Astashyn A, Badretdin A, Bao Y, Blinkova O0, Brover V, Chetvernin V, Choi J, Cox E, Ermolaeva O, Farrell CM, Goldfarb T, Gupta T, Haft D, Hatcher E, Hlavina W, Joardar VS, Kodali VK, Li W, Maglott D, Masterson P, McGarvey KM, Murphy MR, O'Neill K, Pujar S, Rangwala SH, Rausch D, Riddick LD, Schoch C, Shkeda A, Storz SS, Sun H, Thibaud-Nissen F, Tolstoy I, Tully RE, Vatsan AR, Wallin C, Webb D, Wu W, Landrum MJ, Kimchi A, Tatusova T, DiCuccio M, Kitts P, Murphy TD, Pruitt KD Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 44, D733–45 (2016)

• Sourmash
  Brown CT, Irber L sourmash: a library for MinHash sketching of DNA. JOSS 1, 27 (2016)

Step 6 - Sequence Typing

Outputs

Merged Results

Below are results that are concatenated into a single file.

Filename	Description
mlst.tsv	A merged TSV file with mlst results from all samples

mlst

Below is a description of the per-sample results from mlst.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with mlst result, see mlst - Usage for more details

Parameters

Parameter	Description
--scheme	Don't autodetect, force this scheme on all inputs Type: string
--minid	Minimum DNA percent identity of full allelle to consider 'similar' Type: integer, Default: 95
--mincov	Minimum DNA percent coverage to report partial allele at all Type: integer, Default: 10
--minscore	Minimum score out of 100 to match a scheme Type: integer, Default: 50
--nopath	Strip filename paths from FILE column Type: boolean
--mlst_db	A custom MLST database to use, either a tarball or a directory Type: string

Citations

If you use Bactopia and sequence typing results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• csvtk
  Shen, W csvtk: A cross-platform, efficient and practical CSV/TSV toolkit in Golang. (GitHub)

• mlst
  Seemann T mlst: scan contig files against PubMLST typing schemes (GitHub)

• PubMLST.org
  Jolley KA, Bray JE, Maiden MCJ Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications. Wellcome Open Res 3, 124 (2018)

Step 7 - Antibiotic Resistance

Outputs

Merged Results

Below are results that are concatenated into a single file.

Filename	Description
amrfinderplus-genes.tsv	A merged TSV file with AMRFinder+ results using nucleotide inputs
amrfinderplus-proteins.tsv	A merged TSV file with AMRFinder+ results using protein inputs

AMRFinder+

Below is a description of the per-sample results from AMRFinder+.

Filename	Description
-genes.tsv	A TSV file with AMRFinder+ results using nucleotide inputs
-proteins.tsv	A TSV file with AMRFinder+ results using protein inputs

Parameters

Parameter	Description
--ident_min	Minimum proportion of identical amino acids in alignment for hit (0..1) Type: number, Default: -1
--coverage_min	Minimum coverage of the reference protein (0..1) Type: number, Default: 0.5
--organism	Taxonomy group to run additional screens against Type: string
--translation_table	NCBI genetic code for translated BLAST Type: integer, Default: 11
--amrfinder_noplus	Disable running AMRFinder+ with the --plus option Type: boolean
--report_common	Report proteins common to a taxonomy group Type: boolean
--report_all_equal	Report all equally-scoring BLAST and HMM matches Type: boolean
--amrfinder_opts	Extra AMRFinder+ options in quotes. Type: string
--amrfinder_db	A custom AMRFinder+ database to use, either a tarball or a folder Type: string

Citations

If you use Bactopia and antibiotic resistance results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• AMRFinderPlus
  Feldgarden M, Brover V, Haft DH, Prasad AB, Slotta DJ, Tolstoy I, Tyson GH, Zhao S, Hsu C-H, McDermott PF, Tadesse DA, Morales C, Simmons M, Tillman G, Wasilenko J, Folster JP, Klimke W Validating the NCBI AMRFinder Tool and Resistance Gene Database Using Antimicrobial Resistance Genotype-Phenotype Correlations in a Collection of NARMS Isolates. Antimicrob. Agents Chemother. (2019)

• csvtk
  Shen, W csvtk: A cross-platform, efficient and practical CSV/TSV toolkit in Golang. (GitHub)

Step 8 - Merlin

Outputs

Merged Results

Below are results that are concatenated into a single file.

Filename	Description
agrvate.tsv	A merged TSV file with AgrVATE results from all samples
clermontyping.csv	A merged TSV file with ClermonTyping results from all samples
ectyper.tsv	A merged TSV file with ECTyper results from all samples
emmtyper.tsv	A merged TSV file with emmtyper results from all samples
genotyphi.tsv	A merged TSV file with genotyphi results from all samples
hicap.tsv	A merged TSV file with hicap results from all samples
hpsuissero.tsv	A merged TSV file with HpsuisSero results from all samples
kleborate.tsv	A merged TSV file with Kleborate results from all samples
legsta.tsv	A merged TSV file with legsta results from all samples
lissero.tsv	A merged TSV file with LisSero results from all samples
meningotype.tsv	A merged TSV file with meningotype results from all samples
ngmaster.tsv	A merged TSV file with ngmaster results from all samples
pasty.tsv	A merged TSV file with pasty results from all samples
pbptyper.tsv	A merged TSV file with pbptyper results from all samples
seqsero2.tsv	A merged TSV file with seqsero2 results from all samples
seroba.tsv	A merged TSV file with seroba results from all samples
shigapass.csv	A merged CSV file with ShigaPass results from all samples
shigatyper.tsv	A merged TSV file with ShigaTyper results from all samples
shigeifinder.tsv	A merged TSV file with ShigEiFinder results from all samples
sistr.tsv	A merged TSV file with SISTR results from all samples
spatyper.tsv	A merged TSV file with spaTyper results from all samples
ssuissero.tsv	A merged TSV file with SsuisSero results from all samples
sccmec.tsv	A merged TSV file with sccmec results from all samples
stecfinder.tsv	A merged TSV file with stecfinder results from all samples

AgrVATE

Below is a description of the per-sample results from AgrVATE.

Filename	Description
-agr_gp.tab	A detailed report for agr kmer matches
-blastn_log.txt	Log files from programs called by AgrVATE
-summary.tab	A final summary report for agr typing

ClermonTyping

Below is a description of the per-sample results from ClermonTyping.

Filename	Description
<SAMPLE_NAME>.blast.xml	A BLAST XML file with the results of the ClermonTyping analysis
<SAMPLE_NAME>.html	A HTML file with the results of the ClermonTyping analysis
<SAMPLE_NAME>.mash.tsv	A TSV file with the Mash distances
<SAMPLE_NAME>.phylogroups.txt	A TSV file with the final phylogroup assignments

ECTyper

Below is a description of the per-sample results from ECTyper.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with ECTyper result, see ECTyper - Report format for details
blast_output_alleles.txt	Allele report generated from BLAST results

emmtyper

Below is a description of the per-sample results from emmtyper.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with emmtyper result, see emmtyper - Result format for details

hicap

Below is a description of the per-sample results from hicap.

Filename	Description
<SAMPLE_NAME>.gbk	GenBank file and cap locus annotations
<SAMPLE_NAME>.svg	Visualization of annotated cap locus
<SAMPLE_NAME>.tsv	A tab-delimited file with hicap results

HpsuisSero

Below is a description of the per-sample results from HpsuisSero.

Filename	Description
<SAMPLE_NAME>_serotyping_res.tsv	A tab-delimited file with HpsuisSero result

GenoTyphi

Below is a description of the per-sample results from GenoTyphi. A full description of the GenoTyphi output is available at GenoTyphi - Output

Filename	Description
<SAMPLE_NAME>_predictResults.tsv	A tab-delimited file with GenoTyphi results
<SAMPLE_NAME>.csv	The output of mykrobe predict in comma-separated format
<SAMPLE_NAME>.json	The output of mykrobe predict in JSON format

Kleborate

Below is a description of the per-sample results from Kleborate.

Filename	Description
<SAMPLE_NAME>.results.txt	A tab-delimited file with Kleborate result, see Kleborate - Example output for more details.

legsta

Below is a description of the per-sample results from legsta.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with legsta result, see legsta - Output for more details

LisSero

Below is a description of the per-sample results from LisSero.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with LisSero results

Mash

Below is a description of the per-sample results from Mash.

Filename	Description
<SAMPLE_NAME>-dist.txt	A tab-delimited file with mash dist results

meningotype

Below is a description of the per-sample results from meningotype .

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with meningotype result

ngmaster

Below is a description of the per-sample results from ngmaster.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with ngmaster results

pasty

Below is a description of the per-sample results from pasty.

Filename	Description
.blastn.tsv	A tab-delimited file of all blast hits
.details.tsv	A tab-delimited file with details for each serogroup
.tsv	A tab-delimited file with the predicted serogroup

pbptyper

Below is a description of the per-sample results from pbptyper.

Filename	Description
.tblastn.tsv	A tab-delimited file of all blast hits
.tsv	A tab-delimited file with the predicted PBP type

SeqSero2

Below is a description of the per-sample results from SeqSero2.

Filename	Description
<SAMPLE_NAME>_result.tsv	A tab-delimited file with SeqSero2 results
<SAMPLE_NAME>_result.txt	A text file with key-value pairs of SeqSero2 results

Seroba

Below is a description of the per-sample results from Seroba. More details about the outputs are available from Seroba - Output.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with the predicted serotype
detailed_serogroup_info.txt	Detailed information about the predicted results

ShigaPass

Below is a description of the per-sample results from ShigaPass.

Filename	Description
<SAMPLE_NAME>.csv	A CSV file with the predicted Shigella or EIEC serotype

ShigaTyper

Below is a description of the per-sample results from ShigaTyyper.

Filename	Description
<SAMPLE_NAME>-hits.tsv	Detailed statistics about each individual gene hit
<SAMPLE_NAME>.tsv	The final predicted serotype by ShigaTyper

ShigEiFinder

Below is a description of the per-sample results from ShigEiFinder.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with the predicted Shigella or EIEC serotype

SISTR

Below is a description of the per-sample results from SISTR.

Filename	Description
<SAMPLE_NAME>-allele.fasta.gz	A FASTA file of the cgMLST allele search results
<SAMPLE_NAME>-allele.json.gz	JSON formated cgMLST allele search results, see SISTR - cgMLST search results for more details
<SAMPLE_NAME>-cgmlst.csv	A comma-delimited summary of the cgMLST allele search results
<SAMPLE_NAME>.tsv	A tab-delimited file with SISTR results, see SISTR - Primary results for more details

spaTyper

Below is a description of the per-sample results from spaTyper.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with spaTyper result

SsuisSero

Below is a description of the per-sample results from SsuisSero.

Filename	Description
<SAMPLE_NAME>_serotyping_res.tsv	A tab-delimited file with SsuisSero results

sccmec

Below is a description of the per-sample results from sccmec.

Filename	Description
<SAMPLE_NAME>.tsv	A tab-delimited file with sccmec results

TBProfiler

Below is a description of the per-sample results from TBProfiler.

Filename	Description
<SAMPLE_NAME>.results.csv	A CSV formated TBProfiler result file of resistance and strain type
<SAMPLE_NAME>.results.json	A JSON formated TBProfiler result file of resistance and strain type
<SAMPLE_NAME>.results.txt	A text file with TBProfiler results
<SAMPLE_NAME>.bam	BAM file with alignment details
<SAMPLE_NAME>.targets.csq.vcf.gz	VCF with variant info again reference genomes

mashdist

Parameter	Description
--mash_sketch	The reference sequence as a Mash Sketch (.msh file) Type: string
--mash_seed	Seed to provide to the hash function Type: integer, Default: 42
--mash_table	Table output (fields will be blank if they do not meet the p-value threshold) Type: boolean
--mash_m	Minimum copies of each k-mer required to pass noise filter for reads Type: integer, Default: 1
--mash_w	Probability threshold for warning about low k-mer size. Type: number, Default: 0.01
--max_p	Maximum p-value to report. Type: number, Default: 1.0
--max_dist	Maximum distance to report. Type: number, Default: 1.0
--merlin_dist	Maximum distance to report when using Merlin . Type: number, Default: 0.1
--full_merlin	Go full Merlin and run all species-specific tools, no matter the Mash distance Type: boolean
--use_fastqs	Query with FASTQs instead of the assemblies Type: boolean

AgrVATE

Parameter	Description
--typing_only	agr typing only. Skips agr operon extraction and frameshift detection Type: boolean

ClermonTyping

Parameter	Description
--clermon_threshold	Do not use contigs under this size Type: number

ECTyper

Parameter	Description
--opid	Percent identity required for an O antigen allele match Type: integer, Default: 90
--opcov	Minumum percent coverage required for an O antigen allele match Type: integer, Default: 90
--hpid	Percent identity required for an H antigen allele match Type: integer, Default: 95
--hpcov	Minumum percent coverage required for an H antigen allele match Type: integer, Default: 50
--verify	Enable E. coli species verification Type: boolean
--print_alleles	Prints the allele sequences if enabled as the final column Type: boolean

emmtyper

Parameter	Description
--emmtyper_wf	Workflow for emmtyper to use. Type: string, Default: blast
--cluster_distance	Distance between cluster of matches to consider as different clusters Type: integer, Default: 500
--percid	Minimal percent identity of sequence Type: integer, Default: 95
--culling_limit	Total hits to return in a position Type: integer, Default: 5
--mismatch	Threshold for number of mismatch to allow in BLAST hit Type: integer, Default: 5
--align_diff	Threshold for difference between alignment length and subject length in BLAST Type: integer, Default: 5
--gap	Threshold gap to allow in BLAST hit Type: integer, Default: 2
--min_perfect	Minimum size of perfect match at 3 primer end Type: integer, Default: 15
--min_good	Minimum size where there must be 2 matches for each mismatch Type: integer, Default: 15
--max_size	Maximum size of PCR product Type: integer, Default: 2000

hicap

Parameter	Description
--database_dir	Directory containing locus database Type: string
--model_fp	Path to prodigal model Type: string
--full_sequence	Write the full input sequence out to the genbank file rather than just the region surrounding and including the locus Type: boolean
--hicap_debug	hicap will print debug messages Type: boolean
--gene_coverage	Minimum percentage coverage to consider a single gene complete Type: number, Default: 0.8
--gene_identity	Minimum percentage identity to consider a single gene complete Type: number, Default: 0.7
--broken_gene_length	Minimum length to consider a broken gene Type: integer, Default: 60
--broken_gene_identity	Minimum percentage identity to consider a broken gene Type: number, Default: 0.8

GenoTyphi

Parameter	Description
--kmer	K-mer length Type: integer, Default: 21
--min_depth	Minimum depth Type: integer, Default: 1
--model	Genotype model used. Type: string, Default: kmer_count
--report_all_calls	Report all calls Type: boolean
--mykrobe_opts	Extra Mykrobe options in quotes Type: string

Kleborate

Parameter	Description
--kleborate_preset	Preset module to use for Kleborate Type: string, Default: kpsc
--kleborate_opts	Extra options in quotes for Kleborate Type: string

legsta

Parameter	Description
--noheader	Don't print header row Type: boolean

LisSero

Parameter	Description
--min_id	Minimum percent identity to accept a match Type: number, Default: 95.0
--min_cov	Minimum coverage of the gene to accept a match Type: number, Default: 95.0

meningotype

You can use these parameters to fine-tune your meningotype analysis

Parameter	Description
--finetype	perform porA and fetA fine typing Type: boolean
--porB	perform porB sequence typing (NEIS2020) Type: boolean
--bast	perform Bexsero antigen sequence typing (BAST) Type: boolean
--mlst	perform MLST Type: boolean
--all	perform MLST, porA, fetA, porB, BAST typing Type: boolean

ngmaster

Parameter	Description
--csv	output comma-separated format (CSV) rather than tab-separated Type: boolean

pasty

Parameter	Description
--pasty_min_pident	Minimum percent identity to count a hit Type: integer, Default: 95
--pasty_min_coverage	Minimum percent coverage to count a hit Type: integer, Default: 95

pbptyper

Parameter	Description
--pbptyper_min_pident	Minimum percent identity to count a hit Type: integer, Default: 95
--pbptyper_min_coverage	Minimum percent coverage to count a hit Type: integer, Default: 95

SeqSero2

Parameter	Description
--run_mode	Workflow to run. 'a' allele mode, or 'k' k-mer mode Type: string, Default: k
--input_type	Input format to analyze. 'assembly' or 'fastq' Type: string, Default: assembly
--bwa_mode	Algorithms for bwa mapping for allele mode Type: string, Default: mem

SISTR

Parameter	Description
--full_cgmlst	Use the full set of cgMLST alleles which can include highly similar alleles Type: boolean

spaTyper

Parameter	Description
--repeats	List of spa repeats Type: string
--repeat_order	List spa types and order of repeats Type: string
--do_enrich	Do PCR product enrichment Type: boolean

sccmec

Parameter	Description
--hamming	Report the results as hamming distances Type: boolean

TBProfiler Profile

Parameter	Description
--call_whole_genome	Call whole genome Type: boolean
--mapper	Mapping tool to use. If you are using nanopore data it will default to minimap2 Type: string, Default: bwa
--caller	Variant calling tool to use Type: string, Default: freebayes
--calling_params	Extra variant caller options in quotes Type: string
--suspect	Use the suspect suite of tools to add ML predictions Type: boolean
--no_flagstat	Don't collect flagstats Type: boolean
--no_delly	Don't run delly Type: boolean
--tbprofiler_opts	Extra options in quotes for TBProfiler Type: string

Citations

If you use Bactopia and merlin results in your analysis, please cite the following.

• Bactopia
  Petit III RA, Read TD Bactopia - a flexible pipeline for complete analysis of bacterial genomes. mSystems 5 (2020)

• AgrVATE
  Raghuram V. AgrVATE: Rapid identification of Staphylococcus aureus agr locus type and agr operon variants. (GitHub)

• ClermontTyping
  Beghain J, Bridier-Nahmias A, Le Nagard H, Denamur E, Clermont O. ClermonTyping: an easy-to-use and accurate in silico method for Escherichia genus strain phylotyping. Microbial Genomics, 4(7), e000192. (2018)

• csvtk
  Shen, W csvtk: A cross-platform, efficient and practical CSV/TSV toolkit in Golang. (GitHub)

• ECTyper
  Laing C, Bessonov K, Sung S, La Rose C ECTyper - In silico prediction of Escherichia coli serotype (GitHub)

• emmtyper
  Tan A, Seemann T, Lacey D, Davies M, Mcintyre L, Frost H, Williamson D, Gonçalves da Silva A emmtyper - emm Automatic Isolate Labeller (GitHub)

• GenoTyphi
  Wong VK, Baker S, Connor TR, Pickard D, Page AJ, Dave J, Murphy N, Holliman R, Sefton A, Millar M, Dyson ZA, Dougan G, Holt KE, & International Typhoid Consortium. An extended genotyping framework for Salmonella enterica serovar Typhi, the cause of human typhoid Nature Communications 7, 12827. (2016)

• hicap
  Watts SC, Holt KE hicap: in silico serotyping of the Haemophilus influenzae capsule locus. Journal of Clinical Microbiology JCM.00190-19 (2019)

• HpsuisSero
  Lui J HpsuisSero: Rapid Haemophilus parasuis serotyping (GitHub)

• Kleborate
  Lam MMC, Wick RR, Watts, SC, Cerdeira LT, Wyres KL, Holt KE A genomic surveillance framework and genotyping tool for Klebsiella pneumoniae and its related species complex. Nat Commun 12, 4188 (2021)

• legsta
  Seemann T legsta: In silico Legionella pneumophila Sequence Based Typing (GitHub)

• LisSero
  Kwong J, Zhang J, Seeman T, Horan, K, Gonçalves da Silva A LisSero - In silico serotype prediction for Listeria monocytogenes (GitHub)

• Mash
  Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, Phillippy AM Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol 17, 132 (2016)

• meningotype
  Kwong JC, Gonçalves da Silva A, Stinear TP, Howden BP, & Seemann T meningotype: in silico typing for Neisseria meningitidis. (GitHub)

• Mykrobe
  Hunt M, Bradley P, Lapierre SG, Heys S, Thomsit M, Hall MB, Malone KM, Wintringer P, Walker TM, Cirillo DM, Comas I, Farhat MR, Fowler P, Gardy J, Ismail N, Kohl TA, Mathys V, Merker M, Niemann S, Omar SV, Sintchenko V, Smith G, Supply P, Tahseen S, Wilcox M, Arandjelovic I, Peto TEA, Crook, DW, Iqbal Z Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe Wellcome Open Research 4, 191. (2019)

• ngmaster
  Kwong J, Gonçalves da Silva A, Schultz M, Seeman T ngmaster - In silico multi-antigen sequence typing for Neisseria gonorrhoeae (NG-MAST) (GitHub)

• pasty
  Petit III RA pasty: in silico serogrouping of Pseudomonas aeruginosa isolates (GitHub)

• pbptyper
  Petit III RA pbptyper: In silico Penicillin Binding Protein (PBP) typer for Streptococcus pneumoniae assemblies (GitHub)

• SeqSero2
  Zhang S, Den-Bakker HC, Li S, Dinsmore BA, Lane C, Lauer AC, Fields PI, Deng X. SeqSero2: rapid and improved Salmonella serotype determination using whole genome sequencing data. Appl Environ Microbiology 85(23):e01746-19 (2019)

• shigapass
  Yassine I, Hansen EE, Lefèvre S, Ruckly C, Carle I, Lejay-Collin M, Fabre L, Rafei R, Pardos de la Gandara M, Daboussi F, Shahin A, Weill FX ShigaPass: an in silico tool predicting Shigella serotypes from whole-genome sequencing assemblies. Microb Genomics 9(3) (2023)

• ShigaTyper
  Wu Y, Lau HK, Lee T, Lau DK, Payne J In Silico Serotyping Based on Whole-Genome Sequencing Improves the Accuracy of Shigella Identification. Applied and Environmental Microbiology, 85(7). (2019)

• ShigEiFinder
  Zhang X, Payne M, Nguyen T, Kaur S, Lan R Cluster-specific gene markers enhance Shigella and enteroinvasive Escherichia coli in silico serotyping. Microbial Genomics, 7(12). (2021)

• SISTR
  Yoshida CE, Kruczkiewicz P, Laing CR, Lingohr EJ, Gannon VPJ, Nash JHE, Taboada EN The Salmonella In Silico Typing Resource (SISTR): An Open Web-Accessible Tool for Rapidly Typing and Subtyping Draft Salmonella Genome Assemblies. PloS One, 11(1), e0147101. (2016)

• spaTyper
  Sanchez-Herrero JF, and Sullivan M spaTyper: Staphylococcal protein A (spa) characterization pipeline. Zenodo. (2020)

• SsuisSero
  Lui J SsuisSero: Rapid Streptococcus suis serotyping (GitHub)

• sccmec
  Petit III RA, Read TD Staphylococcus aureus viewed from the perspective of 40,000+ genomes. PeerJ 6, e5261 (2018)

• TBProfiler
  Phelan JE, O’Sullivan DM, Machado D, Ramos J, Oppong YEA, Campino S, O’Grady J, McNerney R, Hibberd ML, Viveiros M, Huggett JF, Clark TG Integrating informatics tools and portable sequencing technology for rapid detection of resistance to anti-tuberculous drugs. Genome Med 11, 41 (2019)

Additional Parameters

Optional

These optional parameters can be useful in certain settings.

Parameter	Description
--outdir	Base directory to write results to Type: string, Default: bactopia
--skip_compression	Ouput files will not be compressed Type: boolean
--datasets	The path to cache datasets to Type: string
--keep_all_files	Keeps all analysis files created Type: boolean

Max Job Request

Set the top limit for requested resources for any single job.

Parameter	Description
--max_retry	Maximum times to retry a process before allowing it to fail. Type: integer, Default: 3
--max_cpus	Maximum number of CPUs that can be requested for any single job. Type: integer, Default: 4
--max_memory	Maximum amount of memory that can be requested for any single job. Type: string, Default: 128.GB
--max_time	Maximum amount of time that can be requested for any single job. Type: string, Default: 240.h
--max_downloads	Maximum number of samples to download at a time Type: integer, Default: 3

Nextflow Configuration

to fine-tune your Nextflow setup.

Parameter	Description
--nfconfig	A Nextflow compatible config file for custom profiles, loaded last and will overwrite existing variables if set. Type: string
--publish_dir_mode	Method used to save pipeline results to output directory. Type: string, Default: copy
--infodir	Directory to keep pipeline Nextflow logs and reports. Type: string, Default: ${params.outdir}/pipeline_info
--force	Nextflow will overwrite existing output files. Type: boolean
--cleanup_workdir	After Bactopia is successfully executed, the work directory will be deleted. Type: boolean

Institutional config options

used to describe centralized config profiles. These should not be edited.

Parameter	Description
--custom_config_version	Git commit id for Institutional configs. Type: string, Default: master
--custom_config_base	Base directory for Institutional configs. Type: string, Default: https://raw.githubusercontent.com/nf-core/configs/master
--config_profile_name	Institutional config name. Type: string
--config_profile_description	Institutional config description. Type: string
--config_profile_contact	Institutional config contact information. Type: string
--config_profile_url	Institutional config URL link. Type: string

Nextflow Profile

to fine-tune your Nextflow setup.

Parameter	Description
--condadir	Directory to Nextflow should use for Conda environments Type: string
--registry	Docker registry to pull containers from. Type: string, Default: dockerhub
--datasets_cache	Directory where downloaded datasets should be stored. Type: string, Default: <BACTOPIA_DIR>/data/datasets
--singularity_cache_dir	Directory where remote Singularity images are stored. Type: string
--singularity_pull_docker_container	Instead of directly downloading Singularity images for use with Singularity, force the workflow to pull and convert Docker containers instead. Type: boolean
--force_rebuild	Force overwrite of existing pre-built environments. Type: boolean
--queue	Comma-separated name of the queue(s) to be used by a job scheduler (e.g. AWS Batch or SLURM) Type: string, Default: general,high-memory
--cluster_opts	Additional options to pass to the executor. (e.g. SLURM: '--account=my_acct_name' Type: string
--container_opts	Additional options to pass to Apptainer, Docker, or Singularityu. (e.g. Singularity: '-D pwd' Type: string
--disable_scratch	All intermediate files created on worker nodes of will be transferred to the head node. Type: boolean

Helpful

Uncommonly used parameters that might be useful.

Parameter	Description
--monochrome_logs	Do not use coloured log outputs. Type: boolean
--nfdir	Print directory Nextflow has pulled Bactopia to Type: boolean
--sleep_time	The amount of time (seconds) Nextflow will wait after setting up datasets before execution. Type: integer, Default: 5
--validate_params	Boolean whether to validate parameters against the schema at runtime Type: boolean, Default: True
--help	Display help text. Type: boolean
--wf	Specify which workflow or Bactopia Tool to execute Type: string, Default: bactopia
--list_wfs	List the available workflows and Bactopia Tools to use with '--wf' Type: boolean
--show_hidden_params	Show all params when using --help Type: boolean
--help_all	An alias for --help --show_hidden_params Type: boolean
--version	Display version text. Type: boolean