staramrnf: nextflow pipeline

staramrnf: nextflow pipeline is the nextflow adaptation of staramr

staramr (AMR) scans bacterial genome contigs against the ResFinder, PointFinder, and PlasmidFinder databases (used by the ResFinder webservice and other webservices offered by the Center for Genomic Epidemiology) and compiles a summary report of detected antimicrobial resistance genes. The starinstaramr indicates that it can handle all of the ResFinder, PointFinder, and PlasmidFinder databases.

Table of Contents

• Usage
• Input
• Output
• Parameters

Usage

If you are new to Nextflow and nf-core, please refer to this page on how to set-up Nextflow. Make sure to test your setup with -profile test before running the workflow on actual data.

bash nextflow run phac-nml/staramrnf -r main -latest -profile test,docker --outdir ./results

To run staramrnf, you will need to include both mandatory parameters:

Mandatory Parameters

• --input: a URI to the samplesheet
• --output: the directory for pipeline output

bash nextflow run phac-nml/staramrnf -r main -latest -profile docker --outdir path/output_folder --input path/samplesheet.csv

For more information see usage doc.

Input

Samplesheet Input

You will need to create a samplesheet with information about the samples you would like to analyze before running the pipeline. Use this parameter to specify its location.

bash --input '[path to samplesheet file]'

Samplesheet Description

The input samplesheet requires two columns: sample, contigs with an optional third column species. The species column is used in the selecting of the Pointfinder organism database (empty if "None"). Rows of the sample column within a samplesheet must be unqiue. Any additional columns that aren't named sample, contigs, or species will be ignored by the pipeline.

Note: The parameter --pointfinder_database overrides the species column for all samples.

A final samplesheet file consisting of sample, contigs and species.

csv title="samplesheet.csv" sample,sample_name,contigs,species SAMPLE1,A1,sample1.fastq.gz,Salmonella SAMPLE2,A1,sample2fastq.gz,Escherichia coli SAMPLE3,,sample3.fastq.gz,

| Column | Description | | ------------- | ---------------------------------------------------------------------------------------------------- | | sample | Sample key. Samples should be unique within a samplesheet. Required | | sample_name | Sample name used in outputs (filenames and sample names) | | contigs | Full path to genome contig(s). Uncompressed or gzipped (.gz) fasta file (fna,fa,fasta). Required | | species | Species of genome (see accepted Pointfinder organisms below). Optional |

If sample_name value is left blank for a sample, then the sample value will replace the value. To ensure that all sample_name values are unique, sample will be suffixed to sample_name that are not unique. Non-alphanumeric characters (excluding _,-,.) will be replaced with "_".

An example samplesheet has been provided with the pipeline.

Note: Validated Pointfinder organisms for species include: Enterococcus faecalis, Helicobacter pylori, Salmonella, Enterococcus faecium, Escherichia coli, Campylobacter. Accepted but unvalidated species: Klebsiella, Staphylococcus aureus, Mycobacterium tuberculosis, Neisseria gonorrhoeae, Plasmodium falciparum.

Output

The directories listed below will be created in the --outdir <OUTDIR> directory after the pipeline has finished. All paths are relative to the top-level output directory.

. ├── csvtk ├── pipeline_info └── staramr

The IRIDA Next-compliant JSON output file will be named iridanext.output.json.gz and will be written to the top-level of the results directory. This file is compressed using GZIP and conforms to the IRIDA Next JSON output specifications.

Output Sections

The pipeline is built using Nextflow and processes data using the following steps:

• AMR Bacterial Scans - Scans bacterial genome contigs against the ResFinder, PointFinder, and PlasmidFinder databases and compiles a summary report of detected antimicrobial resistance genes.
• Pipeline information - Report metrics generated during the workflow execution

AMR Bacterial Scans

Pipeline information

Nextflow provides excellent functionality for generating various reports relevant to the running and execution of the pipeline. This will allow you to troubleshoot errors with the running of the pipeline, and also provide you with other information such as launch commands, run times and resource usage.

See the staramr documentation for more details and explanations.

For more information see output doc.

Parameters

StarAMR

For more information on StarAMR parameters

Parameters are run with -- prefix

Example:

bash nextflow run main.nf --outdir ./results --input samplesheet.csv --pid_threshold 99

| Parameters | Description | | -------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | pointfinder_database | Select a single Pointfinder database to use on all samples (overriding samplesheet species). Enterococcus faecium, Enterococcus faecalis, Helicobacter pylori, Salmonella, Campylobacter, Escherichia coli Default: None (or species column) | | plasmidfinder_database | Plasmidfinder database (gram positive or enterobacteriales). Default: Both | | mlst_scheme | Specify scheme name (listed here) Default: Auto-detect | | genome_size_lower_bound | The lower bound for our genome size for the quality metrics Default: 4000000 | | genome_size_upper_bound | The upper bound for our genome size for the quality metrics Default: 6000000 | | minimum_N50_value | The minimum N50 value for the quality metrics Default: 10000 | | minimum_contig_length | The minimum contig length for the quality metrics Default: 300 (bp) | | unacceptable_number_contigs | The minimum, unacceptable number of contigs which are equal to or above the minimum contig length for our quality metrics Default: 1000 | | pid_threshold | BLAST percent identity threshold Default: 98 | | percent_length_overlap_plasmidfinder | The percent length overlap for plasmidfinder results Default: 60 | | percent_length_overlap_resfinder | The percent length overlap for pointfinder results Default: 95 | | no_exclude_genes | Disable the default exclusion of some genes from ResFinder/PointFinder/PlasmidFinder Default: False | | exclude_negatives | Exclude negative results (those susceptible to antimicrobials) Default: False | | exclude_resistance_phenotypes | Exclude predicted antimicrobial resistances Default: False |

Nextflow

For a full set of Nextflow options

bash nextflow run main.nf -help

Nextflow parameters use - prefix

Example -profile

bash nextflow run main.nf -profile test,docker --outdir ./results

| Parameters | Description | | ---------- | ------------------------------------------------------------------------------------------------------- | | profile | Choose a configuration profile (e.g. test, docker, or singularity) | | resume | Execute the script using the cached results, useful to continue executions that was stopped by an error | | revision | Revision of the project to run (either a git branch, tag or commit SHA number) |

Citation

staramr

Bharat A, Petkau A, Avery BP, Chen JC, Folster JP, Carson CA, Kearney A, Nadon C, Mabon P, Thiessen J, Alexander DC, Allen V, El Bailey S, Bekal S, German GJ, Haldane D, Hoang L, Chui L, Minion J, Zahariadis G, Domselaar GV, Reid-Smith RJ, Mulvey MR. Correlation between Phenotypic and In Silico Detection of Antimicrobial Resistance in Salmonella enterica in Canada Using Staramr. Microorganisms. 2022; 10(2):292. https://doi.org/10.3390/microorganisms10020292

Databases used by staramr

Zankari E, Hasman H, Cosentino S, Vestergaard M, Rasmussen S, Lund O, Aarestrup FM, Larsen MV. 2012. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 67:2640–2644. doi: [10.1093/jac/dks261][resfinder-cite]

Zankari E, Allesøe R, Joensen KG, Cavaco LM, Lund O, Aarestrup F. PointFinder: a novel web tool for WGS-based detection of antimicrobial resistance associated with chromosomal point mutations in bacterial pathogens. J Antimicrob Chemother. 2017; 72(10): 2764–8. doi: [10.1093/jac/dkx217][pointfinder-cite]

Carattoli A, Zankari E, Garcia-Fernandez A, Voldby Larsen M, Lund O, Villa L, Aarestrup FM, Hasman H. PlasmidFinder and pMLST: in silico detection and typing of plasmids. Antimicrob. Agents Chemother. 2014. April 28th. doi: [10.1128/AAC.02412-14][plasmidfinder-cite]

Seemann T, MLST Github https://github.com/tseemann/mlst

Jolley KA, Bray JE and Maiden MCJ. Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications [version 1; peer review: 2 approved]. Wellcome Open Res 2018, 3:124. doi: [10.12688/wellcomeopenres.14826.1][mlst-cite]

nf-core

This pipeline uses code and infrastructure developed and maintained by the nf-core community, reused here under the MIT license.

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x. In addition, references of tools and data used in this pipeline are as follows:

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