Short Reads Analysis Mode

Short Reads Analysis Mode#

The short reads analysis mode (--type shortreads) is designed for processing Illumina short-read sequencing data. This mode performs assembly-based CAZyme annotation using MEGAHIT for metagenomic assembly, followed by gene prediction, CAZyme annotation, and abundance calculation.

Overview#

The short reads mode is the default analysis mode and is optimized for Illumina paired-end or single-end sequencing data. It provides comprehensive CAZyme and CGC (CAZyme Gene Cluster) analysis with optional RNA-seq integration for expression analysis.

Workflow#

The short reads workflow consists of the following main steps:

  1. Quality Control (FastQC + TrimGalore) - FastQC quality assessment of raw sequencing reads - TrimGalore adapter trimming and quality filtering

  2. Taxonomic Filtering (Kraken2, optional) - Taxonomic classification using Kraken2 - Extraction of reads matching specified taxonomy (default: human reads, tax ID 9606) - Can be skipped with --skip_kraken_extraction

  3. Read Processing (optional) - Subsampling: Downsample reads before assembly (see Short Reads: Subsampling Mode) - Co-assembly: Combine all samples for joint assembly (see Short Reads: Co-assembly Mode)

  4. Assembly (MEGAHIT) - Metagenomic assembly using MEGAHIT - Default minimum contig length: 1000 bp - Memory usage limited to 50% of available memory

  5. Gene Prediction (Pyrodigal) - Prodigal-based gene finding optimized for metagenomic data - Generates protein sequences (FAA) and gene annotations (GFF)

  6. CAZyme Annotation (run_dbCAN) - CAZyme identification using dbCAN database - CGC (CAZyme Gene Cluster) detection - Substrate prediction

  7. Read Mapping (BWA-MEM) - Mapping of DNA reads back to assembled contigs - Mapping of RNA reads (if provided) for expression analysis - Coverage calculation for genes and CGCs

  8. Abundance Calculation - Gene-level abundance calculation based on read coverage - CGC abundance and visualization - Generation of bar plots and heatmaps

  9. Report Generation (MultiQC) - Aggregated quality control and analysis reports

Usage#

Note

Before running the pipeline, make sure you have cloned the repository. See Nextflow Pipeline: Usage for installation instructions.

Basic Usage#

The simplest command to run short reads analysis (assuming you are in the dbcan-nf directory):

nextflow run main.nf \
  --input samplesheet.csv \
  --outdir results \
  --type shortreads \
  -profile docker \
  --skip_kraken_extraction # based on the database size of kraken2, you can skip this step if the database is too large.

With RNA-seq Data#

When RNA-seq transcriptome data is provided in the samplesheet, the pipeline will automatically:

  • Process RNA reads through quality control

  • Map RNA reads to assembled contigs

  • Calculate RNA-based abundance for expression analysis

  • Generate separate DNA and RNA abundance plots

Note

RNA-seq processing is automatically disabled when using --subsample or --coassembly modes.

Example with RNA-seq:

nextflow run main.nf \
  --input samplesheet_with_rna.csv \
  --outdir results \
  --type shortreads \
  -profile docker

Skipping Steps#

You can skip certain steps if needed:

nextflow run main.nf \
  --input samplesheet.csv \
  --outdir results \
  --type shortreads \
  --skip_fastqc \
  --skip_trimming \
  --skip_kraken_extraction \
  -profile docker

Advanced Options#

Using custom databases:

nextflow run main.nf \
  --input samplesheet.csv \
  --outdir results \
  --type shortreads \
  --dbcan_db /path/to/dbcan_database \
  --kraken_db /path/to/kraken_database \
  -profile docker

Subsampling and Co-assembly#

The short reads mode supports two special processing options:

These modes are mutually exclusive and cannot be used together.

Output Files#

The pipeline generates output files organized in the following directory structure:

Assembly Results#

  • megahit/ - *_contigs.fa.gz: Assembled contigs in FASTA format (gzipped) - Assembly statistics and reports

Gene Prediction#

  • pyrodigal/ - *.faa.gz: Predicted protein sequences (gzipped) - *.gff.gz: Gene annotations in GFF format (gzipped)

CAZyme Annotation#

  • rundbcan/ - *_dbcan/: Directory containing all run_dbCAN results

    Files in this directory:

    • overview.tsv: CAZyme annotation overview

    • dbCAN_hmm_results.tsv: HMM-based CAZyme predictions

    • dbCANsub_hmm_results.tsv: Subfamily predictions

    • diamond.out: DIAMOND search results

    • *_cgc.gff: CGC annotations

    • *_cgc_standard_out.tsv: CGC standard output

    • *_substrate_prediction.tsv: Substrate predictions

    • *_synteny_pdf/: Synteny plots for CGCs

Read Mapping#

  • bwa/: BWA index files

  • bwa_index_mem/: BAM files from read mapping - *.bam: Aligned reads - *.bam.bai: BAM index files

Coverage and Abundance#

  • dbcan_utils_cal_coverage/ - *_depth.txt: Gene coverage depth files

  • dbcan_utils_cal_abund/ - *_abund/: Abundance calculation results

    Files in this directory:

    • *_abund.txt: Gene abundance values

    • *_cgc_abund.txt: CGC abundance values

  • dbcan_plot/ - *_pdf/: Visualization plots

    Files in this directory:

    • heatmap.pdf: Abundance heatmap

    • ec.pdf: EC number distribution

    • family.pdf: CAZyme family distribution

    • subfamily.pdf: Subfamily distribution

  • cgc_depth_plot/ - *_cgc_depth.tsv: CGC depth coverage data - *_cgc_depth.pdf: CGC depth plots

Quality Control#

  • fastqc/: FastQC reports (if not skipped)

  • trimgalore/: TrimGalore reports (if not skipped)

  • multiqc/: MultiQC aggregated report

Pipeline Information#

  • pipeline_info/: Execution reports, parameters, and software versions

Key Features#

  • Dual Analysis: Supports both DNA and RNA-seq data for comprehensive analysis

  • Flexible Processing: Optional subsampling and co-assembly modes

  • Comprehensive Annotation: CAZyme identification, CGC detection, and substrate prediction

  • Abundance Calculation: Gene-level and CGC-level abundance with visualization

  • Quality Control: Integrated QC pipeline with MultiQC reporting

Example Results#

For example visualizations and results from short reads mode analysis, see Nextflow Pipeline: Results Examples.

See Also#

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