README.md

metagWGS

Introduction

metagWGS is a Nextflow bioinformatics analysis pipeline used for metagenomic Whole Genome Shotgun sequencing data (Illumina HiSeq3000 or NovaSeq, paired, 2*150bp).

Pipeline graphical representation

The workflow processes raw data from .fastq or .fastq.gz inputs and do the modules represented into this figure:

metagWGS steps

metagWGS is splitted into different steps that correspond to different parts of the bioinformatics analysis:

• 01_clean_qc (can ke skipped)
  • trims adapters sequences and deletes low quality reads (Cutadapt, Sickle)
  • suppresses host contaminants (BWA + Samtools + Bedtools)
  • controls the quality of raw and cleaned data (FastQC)
  • makes a taxonomic classification of cleaned reads (Kaiju MEM + kronaTools + Generate_barplot_kaiju.py + merge_kaiju_results.py)
• 02_assembly
  • assembles cleaned reads (combined with 01_clean_qc step) or raw reads (combined with --skip_01_clean_qc parameter) (metaSPAdes or Megahit)
  • assesses the quality of assembly (metaQUAST)
  • deduplicates cleaned reads (combined with 01_clean_qc step) or raw reads (combined with --skip_01_clean_qc parameter) (BWA + Samtools + Bedtools)
• 03_filtering (can be skipped)
  • filters contigs with low CPM value (Filter_contig_per_cpm.py + metaQUAST)
• 04_structural_annot
  • makes a structural annotation of genes (Prokka + Rename_contigs_and_genes.py)
• 05_alignment
  • aligns reads to the contigs (BWA + Samtools)
  • aligns the protein sequence of genes against a protein database (DIAMOND)
• 06_func_annot
  • makes a sample and global clustering of genes (cd-hit-est + cd_hit_produce_table_clstr.py)
  • quantifies reads that align with the genes (featureCounts + Quantification_clusters.py)
  • makes a functional annotation of genes and a quantification of reads by function (eggNOG-mapper + best_bitscore_diamond.py + merge_abundance_and_functional_annotations.py + quantification_by_functional_annotation.py)
• 07_taxo_affi
  • taxonomically affiliates the genes (Samtools + aln2taxaffi.py)
  • taxonomically affiliates the contigs (Samtools + aln2taxaffi.py)
  • counts the number of reads and contigs, for each taxonomic affiliation, per taxonomic level (Samtools + merge_contig_quantif_perlineage.py + quantification_by_contig_lineage.py)
• 08_binning from nf-core/mag 1.0.0
  • makes binning of contigs (MetaBAT2)
  • assesses bins (BUSCO + metaQUAST + summary_busco.py and combine_tables.py from nf-core/mag)
  • taxonomically affiliates the bins (BAT)

A report html file is generated at the end of the workflow with MultiQC.

The pipeline is built using Nextflow, a bioinformatics workflow tool to run tasks across multiple compute infrastructures in a very portable manner.

Three Singularity containers are available making installation trivial and results highly reproducible.

Documentation

metagWGS documentation is available here.

License

metagWGS is distributed under the GNU General Public License v3.

Copyright

2021 INRAE

Funded by

Anti-Selfish (Labex ECOFECT – N° 00002455-CT15000562) France Génomique National Infrastructure (funded as part of Investissement d’avenir program managed by Agence Nationale de la Recherche, contract ANR-10-INBS-09) With participation of SeqOccIn members financed by FEDER-FSE MIDI-PYRENEES ET GARONNE 2014-2020.

Citation

metagWGS has been presented at JOBIM 2020:

Poster "Whole metagenome analysis with metagWGS", J. Fourquet, C. Noirot, C. Klopp, P. Pinton, S. Combes, C. Hoede, G. Pascal.

https://www.sfbi.fr/sites/sfbi.fr/files/jobim/jobim2020/posters/compressed/jobim2020_poster_9.pdf

metagWGS has been presented at JOBIM 2019 and at Genotoul Biostat Bioinfo day:

Poster "Whole metagenome analysis with metagWGS", J. Fourquet, A. Chaubet, H. Chiapello, C. Gaspin, M. Haenni, C. Klopp, A. Lupo, J. Mainguy, C. Noirot, T. Rochegue, M. Zytnicki, T. Ferry, C. Hoede.