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Taxonomic classification of reads and abundance estimation of species in metagenomic samples

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kraken2

metashot/kraken2 is a workflow for the taxonomic classification of reads and the abundance estimation of species in metagenomic samples.

Main features

  • Input: single-end, paired-end (also interleaved) Illumina sequences (gzip and bzip2 compressed FASTA or FASTQ also supported);
  • Histogram text files (for each input sample) of base frequency, quality scores, GC content, average quality and length are generated from input reads using bbduk;
  • Taxonomic classification using Kraken 2;
  • Abundance estimation for each taxonomic level using Bracken.

Quick start

  1. Install Docker (or Singulariry) and Nextflow (see Dependences);
  2. Download and extract/unzip a Kraken 2 / Bracken database available at https://benlangmead.github.io/aws-indexes/k2;
  3. Start running the analysis:
nextflow run metashot/kraken2 \
  --reads '*_R{1,2}.fastq.gz' \
  --kraken2_db k2db \
  --read_len 100 \
  --outdir results

Parameters

See the file nextflow.config for the complete list of parameters.

Output

The files and directories listed below will be created in the results directory after the pipeline has finished.

Main outputs

  • combined.kraken2.report: combined kraken2 report;
  • combined.kraken2.mpa: combined kraken2 report in mpa (MetaPhlAn) format;
  • combined_bracken: contains the combined bracken outputs (one file for each taxonomic level, from Domain D to Species S);
  • combine_bracken_reports: same as combined_bracken but in kraken2 report format;
  • combine_bracken_mpa: same as combined_bracken but in mpa (MetaPhlAn) format;

Secondary outputs

  • raw_reads_stats: base frequency, quality scores, gc content, average quality and length for each input sample;
  • kraken2: kraken2 output for each sample.
  • bracken: bracken output for each taxonomic level (from Domain D to Species S) for each sample.

Memory requirements

Kraken 2 requires enough free memory to hold the index in RAM. If the index size is 47 GB (standard database, 2020/09/19) you will need slightly more than that free in RAM (set the --max_memory parameter to 64.GB).

Please refer to System requirements for the complete list of system requirements options.

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Taxonomic classification of reads and abundance estimation of species in metagenomic samples

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