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uk_0tR*k9z&YLM_V+1e2a=091A8wx7B+Scb_O_7QekNkxc?7J{KDY? literal 0 HcmV?d00001 From ffe22e7307246d35805195bb0cca783d4cbd8cee Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Thu, 19 Oct 2023 11:04:22 +0100 Subject: [PATCH 2/4] Creating 10.21105.joss.05397.crossref.xml --- joss.05397/10.21105.joss.05397.crossref.xml | 391 ++++++++++++++++++++ 1 file changed, 391 insertions(+) create mode 100644 joss.05397/10.21105.joss.05397.crossref.xml diff --git a/joss.05397/10.21105.joss.05397.crossref.xml b/joss.05397/10.21105.joss.05397.crossref.xml new file mode 100644 index 0000000000..f56e791f38 --- /dev/null +++ b/joss.05397/10.21105.joss.05397.crossref.xml @@ -0,0 +1,391 @@ + + + + 20231019T100359-d2ff7b2afc7d410ff5b1b31b2c4d79ed578b8c85 + 20231019100359 + + JOSS Admin + admin@theoj.org + + The Open Journal + + + + + Journal of Open Source Software + JOSS + 2475-9066 + + 10.21105/joss + https://joss.theoj.org + + + + + 10 + 2023 + + + 8 + + 90 + + + + Baargin: a Nextflow workflow for the automatic analysis +of bacterial genomics data with a focus on Antimicrobial +Resistance + + + + Juliette + Hayer + https://orcid.org/0000-0003-4899-9637 + + + Jacques + Dainat + https://orcid.org/0000-0002-6629-0173 + + + Ella + Marcy + https://orcid.org/0009-0002-6000-1665 + + + Anne-Laure + Bañuls + https://orcid.org/0000-0002-2106-8667 + + + + 10 + 19 + 2023 + + + 5397 + + + 10.21105/joss.05397 + + + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + http://creativecommons.org/licenses/by/4.0/ + + + + Software archive + 10.5281/zenodo.8386399 + + + GitHub review issue + https://github.com/openjournals/joss-reviews/issues/5397 + + + + 10.21105/joss.05397 + https://joss.theoj.org/papers/10.21105/joss.05397 + + + https://joss.theoj.org/papers/10.21105/joss.05397.pdf + + + + + + The staggering death toll of drug-resistant +bacteria + Thompson + Nature + 10.1038/D41586-022-00228-X + 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Bioinformatics, 31(22), 3691–3693. +https://doi.org/10.1093/BIOINFORMATICS/BTV421 + + + + + + From 68160603e71eaa01c2811c5f6bb9df7b0f4c81b1 Mon Sep 17 00:00:00 2001 From: The Open Journals editorial robot <89919391+editorialbot@users.noreply.github.com> Date: Thu, 19 Oct 2023 11:04:23 +0100 Subject: [PATCH 3/4] Creating 10.21105.joss.05397.jats --- joss.05397/10.21105.joss.05397.jats | 770 ++++++++++++++++++++++++++++ 1 file changed, 770 insertions(+) create mode 100644 joss.05397/10.21105.joss.05397.jats diff --git a/joss.05397/10.21105.joss.05397.jats b/joss.05397/10.21105.joss.05397.jats new file mode 100644 index 0000000000..b0833e049b --- /dev/null +++ b/joss.05397/10.21105.joss.05397.jats @@ -0,0 +1,770 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +5397 +10.21105/joss.05397 + +Baargin: a Nextflow workflow for the automatic analysis +of bacterial genomics data with a focus on Antimicrobial +Resistance + + + +https://orcid.org/0000-0003-4899-9637 + +Hayer +Juliette + + + +* + + +https://orcid.org/0000-0002-6629-0173 + +Dainat +Jacques + + + + +https://orcid.org/0009-0002-6000-1665 + +Marcy +Ella + + + + + +https://orcid.org/0000-0002-2106-8667 + +Bañuls +Anne-Laure + + + + + + +MIVEGEC, University of Montpellier, IRD, CNRS, 34394, +Montpellier, France + + + + +Laboratoire Mixte International Drug Resistance in +Southeast Asia + + + + +Centre Hospitalier Universitaire (CHU) Lapeyronie, +Montpellier, France + + + + +* E-mail: + + +18 +2 +2023 + +8 +90 +5397 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Nextflow +Whole Genome Shotgun +Genomics +Long reads sequencing technology +Short reads sequencing technology +Antimicrobial Resistance +Pangenome + + + + + + Summary +

The emergence and development of Antimicrobial Resistance (AMR) is + a global health problem, that could cause about 10 million deaths + yearly by 2050 + (Thompson, + 2022). The study of the genomes of these (multi)resistant + bacterial strains is of high importance to understand emergence and + circulation of the resistance. In the past couple of decades, high + throughput sequencing technologies have seriously improved and it has + become more affordable to sequence the full genomes of hundreds of + bacterial strains at a time. As a counterpart, these experiments + produce large amount of data that needs to be analysed by various + bioinformatics methods and tools for reconstructing the genomes and + therefore identify their specific features and the genetic + determinants of the AMR. For automating the bioinformatics analysis of + multiple strains, we have developed a Nextflow + (DI + Tommaso et al., 2017) workflow called baargin + (Bacterial Assembly and Antimicrobial Resistance Genes detection In + Nextflow) + https://github.com/jhayer/baargin. + It enables to conduct sequencing reads quality control, genome + assembly and annotation, Multi-Locus Sequence Typing and plasmid + identification, as well as antimicrobial resistance determinants + detection, and pangenome analysis. The use of Nextflow, a workflow + management system, makes our workflow portable, flexible, and able to + conduct reproducible analyses.

+
+ + Statement of need +

High Throughput Sequencing technologies produce a significant + amount of data and researchers are producing genomics data all over + the world on a daily basis. These technologies are notably used for + studying bacterial genomes in order to understand the spread of + bacterial pathogens and their resistance to antibiotics. In the + bacterial genomics field, it is possible to sequence the DNA from + multiple bacterial strains at the same time. The analysis of these + sequencing data requires the use of a wide range of bioinformatics + programs to be able to identify the genes and their functions, and + among those, the genes and mutations conferring resistance to + antimicrobial drugs. In order to make the results of these analyses + comparable, it is crucial to standardise, automate and parallelise all + the steps. The baargin workflow allows the user to + perform a complete in silico analysis of bacterial + genomes, from the quality control of the raw data, to the detection of + AMR genes and mutations, on multiple datasets of the same bacterial + species in parallel. It compiles and summarise the results from all + the analysis steps, allowing comparative studies. As a last step, + baargin performs a pangenome analysis of all the + strains provided, producing the basis for the construction of a + phylogenetic tree. The use of Nextflow and containers ensures the + reproducibility of the data analysis. Only few bacterial genomics + workflows are available, like Bactopia + (Petit + III, 2020), which is highly flexible and complete in term of + tools available. Therefore, we needed a lighter workflow, with only a + few tools and databases installed for our collaborators that have only + limited computing resources and storage. Also, + baargin is specifically designed for detecting AMR + genes and plasmid features, and include a decontamination step of the + assembly, allowing the downstream analyses to be performed especially + on the contigs belonging to the targeted species.

+
+ + Materials and Methods + + Features +

Baargin is designed to automatically parallelise workflow steps. + It does not require manual intervention from the users between + steps. Each workflow step, called process, uses containers, via + Docker or Singularity, which also greatly improves traceability and + reproducibility. Additional processes can be easily added in the + future as the workflow is designed in modules, making it flexible + for adding or removing steps.

+
+ + Workflow +

[fig:Figure1] + describes the workflow:

+ + +

Input can be either a folder containing paired-end short + reads (fastq format), a folder containing already assembled + contigs (fasta format files), or an index file containing the + paths to pair-end short reads (fastq files) and to long reads + (ONT, fastq file) for the same sample/strain in order to perform + hybrid assembly. If assembled contigs are provided, the analysis + will start at step 4.

+
+ +

Quality check and adapters removal is performed on the short + reads using Fastp + (Chen + et al., 2018).

+
+ +

De novo assembly is run using SPAdes + (Prjibelski + et al., 2020) if only short reads were provided, and with + Unicycler + (Wick + et al., 2017) for a hybrid assembly when short and long + reads are provided.

+
+ +

Taxonomic assignment of the contigs is performed using + Kraken2 + (Wood + et al., 2019) and the contigs classified at the taxonomic + level provided by the user (with the taxid, and including the + children taxa) are retrieved and therefore named as + “deconta” for decontaminated contigs + (Lu + et al., 2022). The dataset containing all the contigs are + named as “raw”. From here all the steps except + the annotation (8) will be performed on both sets of contigs + “raw” and “deconta”.

+
+ +

A quality check of the assembly is conducted using Quast + (Gurevich + et al., 2013) and BUSCO + (Manni + et al., 2021). For BUSCO, the users have the possibility + to specify the taxonomic lineage database to use for searching + the housekeeping genes (at the class level of the strain to + analyse for example: + enterobacterales_odb10)

+
+ +

The contigs (raw and + deconta) are then screened to identify the + sequence type of the strain using the MLST tool (Multi-Locus + Sequence Typing) + (Seemann, + 2022).

+
+ +

The contigs are subsequently submitted to plasmid + identification using PlasmidFinder + (Carattoli + et al., 2014) and additionally with Platon if the user + provides a database for it + (Schwengers + et al., 2020).

+
+ +

Antimicrobial Resistance Genes (ARGs) are then searched in + the contigs using both CARD RGI + (Alcock + et al., 2023) and the NCBI AMRFinderPlus + (Feldgarden + et al., 2021). For certain species only, AMRFinderPlus + can also detect some mutations conferring resistance, if the + user provides that option.

+
+ +

A genome annotation is performed on the + deconta contigs using Prokka by default + (Seemann, + 2014), or using Bakta + (Schwengers + et al., 2021) if the user provides a database for it.

+
+ +

Once all the strains datasets provided are annotated a + pangenome analysis is done using Roary + (Page + et al., 2015).

+
+
+
+ + Output +

The results are located in a nested folder architecture. For each + dataset, a folder with the sampleID is created, and contains 5 + subfolders: - qc - assembly - AMR - annotation - plasmids These + subfolders contain the main outputs from the concerned analyses. + Additionally, at the root of the results folder (indicated by the + user) 2 folders are created: pangenome, containing + the results for Roary, and compile_results that + contains summary files for each analysis where the results for all + datasets provided in input are compiled as presence/absence matrices + for further comparative analyses.

+
+
+ + Discussion and conclusions +

We presented here an easy-to-use workflow for Bacterial Assembly + and Antimicrobial Resistance Genes detection In Nextflow: + baargin. It allows the users to analyse genomic + datasets from short and long sequencing reads, of several bacterial + strains from the same species in one command line. The workflow will + automatically assemble the genomes, check for contamination and + specifically extract the sequences that belong to the expected taxon. + It will then identify their sequence type and screen the assemblies + for plasmids sequences and ARGs. The fact that + baargin is implemented in Nextflow and is based on + containers makes the analyses reproducible. Its modular design makes + it easy to customise and extend, by adding new modules for new + processes.

+
+ + Figures + +

Flowchart of baargin + workflow.

+ +
+
+ + Acknowledgements +

We acknowledge contributions from Son Thai Nguyen and Julio + Benavides during the development of this workflow.

+

The authors acknowledge the ISO 9001 certified IRD i-Trop HPC + (South Green Platform) at IRD Montpellier for providing HPC resources + to develop the workflow reported within this paper. + https://bioinfo.ird.fr + http://www.southgreen.fr

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