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Metagenome assembled genomes generation workflow

Summary

The workflow is based on IMG MAGs pipeline1 for metagenome assembled genomes generation. It takes assembled contigs, bam file from reads mapping to contigs and contigs annotations result to associate groups of contigs as deriving from a seemingly coherent microbial species (binning) and evaluted by checkM, gtdb-tk and eukcc.

Required Database

    wget https://data.ace.uq.edu.au/public/CheckM_databases/checkm_data_2015_01_16.tar.gz
    tar -xvzf checkm_data_2015_01_16.tar.gz
    mkdir -p refdata/CheckM_DB && tar -xvzf checkm_data_2015_01_16.tar.gz -C refdata/CheckM_DB
    rm checkm_data_2015_01_16.tar.gz
    wget https://data.gtdb.ecogenomic.org/releases/release214/214.0/auxillary_files/gtdbtk_r214_data.tar.gz
    mkdir -p refdata/GTDBTK_DB && tar -xvzf gtdbtk_r214_data.tar.gz 
    mv release214 refdata/GTDBTK_DB
    rm gtdbtk_r214_data.tar.gz
    wget http://ftp.ebi.ac.uk/pub/databases/metagenomics/eukcc/eukcc2_db_ver_1.2.tar.gz
    tar -xvzf eukcc2_db_ver_1.2.tar.gz
    mv eukcc2_db_ver_1.2 EUKCC2_DB
    rm eukcc2_db_ver_1.2.tar.gz

Running Workflow in Cromwell

Description of the files:

  • .wdl file: the WDL file for workflow definition
  • .json file: the example input for the workflow
  • .conf file: the conf file for running Cromwell.
  • .sh file: the shell script for running the example workflow (sbatch)

The Docker images

microbiomedata/nmdc_mbin

microbiomedata/nmdc_mbin_vis

Input files

A json files with following entries:

  1. Project Name
  2. Metagenome Assembled Contig fasta file
  3. Sam/Bam file from reads mapping back to contigs.
  4. Contigs functional annotation result in gff format
  5. Contigs functional annotated protein FASTA file
  6. Tab delimited file for COG annotation.
  7. Tab delimited file for EC annotation.
  8. Tab delimited file for KO annotation.
  9. Tab delimited file for PFAM annotation.
  10. Tab delimited file for TIGRFAM annotation.
  11. Tab delimited file for CRISPR annotation.
  12. Tab delimited file for Gene Product name assignment.
  13. Tab delimited file for Gene Phylogeny assignment.
  14. Tab delimited file for Contig/Scaffold lineage.
  15. GTDBTK Database
  16. CheckM Database
  17. (optional) nmdc_mags.threads: The number of threads used by metabat/samtools/checkm/gtdbtk. default: 64
  18. (optional) nmdc_mags.pthreads: The number of threads used by pplacer (Use lower number to reduce the memory usage) default: 1
  19. (optional) nmdc_mags.map_file: MAP file containing mapping of contig headers to annotation IDs
{
    "nmdc_mags.proj_name": "nmdc_wfmgan-xx-xxxxxxxx",
    "nmdc_mags.contig_file": "/path/to/Assembly/nmdc_wfmgas-xx-xxxxxxx_contigs.fna",
    "nmdc_mags.sam_file": "/path/to/Assembly/nmdc_wfmgas-xx-xxxxxxx_pairedMapped_sorted.bam",
    "nmdc_mags.gff_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_functional_annotation.gff",
    "nmdc_mags.proteins_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_proteins.faa",
    "nmdc_mags.cog_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_cog.gff",
    "nmdc_mags.ec_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_ec.tsv",
    "nmdc_mags.ko_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_ko.tsv",
    "nmdc_mags.pfam_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_pfam.gff",
    "nmdc_mags.tigrfam_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxxtigrfam.gff",
    "nmdc_mags.crispr_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_crt.crisprs,
    "nmdc_mags.product_names_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_product_names.tsv",
    "nmdc_mags.gene_phylogeny_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_gene_phylogeny.tsv",
    "nmdc_mags.lineage_file": "/path/to/Annotation/nmdc_wfmgas-xx-xxxxxxx_scaffold_lineage.tsv",
    "nmdc_mags.gtdbtk_db": "refdata/GTDBTK_DB",
    "nmdc_mags.checkm_db": "refdata/CheckM_DB"
}

Output files

The output will have a bunch of output directories, files, including statistical numbers, status log and a shell script to reproduce the steps etc.

The final MiMAG output includes following files.

|-- project_name_mags_stats.json
|-- project_name_hqmq_bin.zip
|-- project_name_lq_bin.zip
|-- project_name_bin.info
|-- project_name_bins.lowDepth.fa
|-- project_name_bins.tooShort.fa
|-- project_name_bins.unbinned.fa
|-- project_name_checkm_qa.out
|-- project_name_gtdbtk.ar122.summary.tsv
|-- project_name_gtdbtk.bac122.summary.tsv
|-- project_name_heatmap.pdf  (The Heatmap presents the pdf file containing the KO analysis results for metagenome bins)
|-- project_name_barplot.pdf  (The Bar chart presents the pdf file containing the KO analysis results for metagenome bins
|-- project_name_kronaplot.html  (The Krona plot presents the HTML file containing the KO analysis results for metagenome bins)

Citation

  1. Chen IA, Chu K, Palaniappan K, et al. IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 2019;47(D1):D666‐D677. doi:10.1093/nar/gky901
  2. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25(7):1043‐1055. doi:10.1101/gr.186072.114
  3. Pierre-Alain Chaumeil, Aaron J Mussig, Philip Hugenholtz, Donovan H Parks, GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database, Bioinformatics, Volume 36, Issue 6, 15 March 2020, Pages 1925–1927, doi.org/10.1093/bioinformatics/btz848
  4. Saary, Paul, Alex L. Mitchell, and Robert D. Finn. "Estimating the quality of eukaryotic genomes recovered from metagenomic analysis with EukCC." Genome biology 21.1 (2020): 1-21. doi.org/10.1186/s13059-020-02155-4