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Pipeline for running routine quality control analyses on illumina sequence data

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Routine Sequence QC

Tests

A generic pipeline that can be run routinely on all Illumina sequence runs, regardless of the project or organism of interest.

  • Sequence quality information
  • Possible contamination

Analyses

  • Parse run-level QC statistics from the 'InterOp' directory and write to .csv and .json format.
  • FastQC: sample-level sequence quality metrics
  • Kraken2 + Bracken: Taxonomic classification of reads. Estimation of relative abundances of taxonomic groups (genus, species) in each sample.
  • MultiQC: Collect several QC metrics into a single interactive HTML report.

Usage

nextflow run BCCDC-PHL/routine-sequence-qc \
  [--instrument_type nextseq] \
  [--kraken2_db /path/to/kraken2_db] \
  [--bracken_db /path/to/bracken_db] \
  --run_dir <your illumina run directory> \
  --outdir <output directory>

Outputs

<outdir>
├── abundance_top_n
│   ├── top_3_abundances_genus.csv
│   └── top_5_abundances_species.csv
├── bracken
│   ├── <sample_id>_Genus_bracken_abundances.tsv
│   ├── <sample_id>_Genus_bracken.txt
│   ├── <sample_id>_Species_bracken_abundances.tsv
│   ├── <sample_id>_Species_bracken.txt
│   ├── ...
├── fastqc
│   ├── <sample_id>_R1_fastqc
│   ├── <sample_id>_R2_fastqc
│   ├── ...
├── interop_summary
│   ├── interop_index-summary.csv
│   └── interop_summary.csv
├── kraken2
│   ├── <sample_id>_kraken2.txt
│   ├── ...
├── multiqc
│   ├── multiqc_data
│   └── multiqc_report.html
└── parse_sample_sheet
    └── sample_sheet.json

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Pipeline for running routine quality control analyses on illumina sequence data

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  • Python 52.4%
  • Nextflow 26.8%
  • Shell 20.8%