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.

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

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.

--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.

sample,contigs,species
SAMPLE1,sample1.fastq.gz,Salmonella
SAMPLE2,sample2fastq.gz,Escherichia coli
SAMPLE3,sample3.fastq.gz,

Column	Description
sample	Custom sample name. Samples should be unique within a samplesheet. Required
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

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

Output files

For More information see staramr output description

• staramr/
  • StarAMR search results for each sample:
    • sample_detailed_summary.staramr.tsv : A detailed summary of all detected AMR genes/mutations/plasmids/sequence type in each genome, one gene per line.
    • sample_mlst.staramr.tsv : A tabular file of each multi-locus sequence type (MLST) and it's corresponding locus/alleles, one genome per line.
    • sample_plasmidfinder.staramr.tsv :A tabular file of each AMR plasmid type and additional BLAST information from the PlasmidFinder database, one plasmid type per line.
    • sample_pointfinder.staramr.tsv : A tabular file of each AMR point mutation and additional BLAST information from the PointFinder database, one gene per line.(Pointfinder organisms)
    • sample_resfinder.staramr.tsv : A tabular file of each AMR gene and additional BLAST information from the ResFinder database, one gene per line.
    • sample_results.staramr.xlsx : An Excel spreadsheet containing the previous 6 files as separate worksheets.
    • sample_settings.staramr.txt :The command-line, database versions, and other settings used to run staramr.
    • sample_summary.staramr.tsv : A summary of all detected AMR genes/mutations/plasmids/sequence type in each genome, one genome per line. A series of descriptive statistics is also provided for each genome as well as feedback for whether or not the genome passes several quality metrics and if not, feedback on why the genome fails.
• csvtk/
  • Combine results from all samples into a single report
    • merged_detailed_summary.staramr.tsv
    • merged_mlst.staramr.tsv
    • merged_plasmidfinder.staramr.tsv
    • merged_pointfinder.staramr.tsv (Pointfinder organisms)
    • merged_resfinder.staramr.tsv
    • merged_summary.staramr.tsv

Pipeline information

Output files

• pipeline_info/
  • Reports generated by Nextflow: execution_report.html, execution_timeline.html, execution_trace.txt and pipeline_dag.dot/pipeline_dag.svg.
  • Reports generated by the pipeline: pipeline_report.html, pipeline_report.txt and software_versions.yml. The pipeline_report* files will only be present if the --email / --email_on_fail parameter's are used when running the pipeline.
  • Reformatted samplesheet files used as input to the pipeline: samplesheet.valid.csv.
  • Parameters used by the pipeline run: params.json.

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:

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

nextflow run main.nf -help

Nextflow parameters use - prefix

Example -profile

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:

Legal

Copyright 2024 Government of Canada

Licensed under the MIT License (the "License"); you may not use this work except in compliance with the License. You may obtain a copy of the License at:

https://opensource.org/license/mit/

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.