sequana-downsampling 0.10.0

Downsample NGS data sets (FastQ/FastA) using the Sequana framework

This is the downsampling pipeline from the Sequana project.

Overview:

Downsample NGS data sets (FastQ or FastA).

Input:

A set of FastQ or FastA files (single or paired-end).

Output:

Downsampled FastQ or FastA files.

Status:

Production

Citation:

Cokelaer et al, (2017), ‘Sequana’: a Set of Snakemake NGS pipelines, Journal of Open Source Software, 2(16), 352, JOSS DOI https://doi.org/10.21105/joss.00352

Installation

pip install sequana_downsampling --upgrade

You will also need pigz available on your PATH.

Quick Start

1. Set up the pipeline:

sequana_downsampling --input-directory DATAPATH

2. Run the pipeline:

cd downsampling
bash downsampling.sh

Usage

sequana_downsampling --help

Key pipeline-specific options:

--downsampling-input-format

Input format: fastq (default), fasta, or sam.

--downsampling-method

random (default, keeps a fixed number of reads) or random_pct (keeps a percentage of reads).

--downsampling-max-entries

Number of reads to keep when using random (default: 1000).

--downsampling-percent

Percentage of reads to keep when using random_pct (default: 10).

--downsampling-threads

Number of threads used by pigz to compress output (default: 4).

Examples:

sequana_downsampling --input-directory DATAPATH \
    --downsampling-method random --downsampling-max-entries 100

sequana_downsampling --input-directory DATAPATH \
    --downsampling-method random_pct --downsampling-percent 10 \
    --downsampling-input-format fasta --input-pattern "*.fasta"

Run on a SLURM cluster:

cd downsampling
sbatch downsampling.sh

Or drive Snakemake directly:

snakemake -s downsampling.rules --cores 4 --stats stats.txt

Requirements

The following tools must be available (install via conda/bioconda):

mamba env create -f environment.yml

• sequana — FastQ/FastA selection (Python API)

• pigz — parallel gzip compression of outputs

Pipeline overview

The pipeline randomly selects reads from the input files (single or paired). If the inputs are paired, the one-to-one mapping between R1 and R2 is preserved. FastQ inputs can be gzipped; outputs are gzipped with pigz. FastA inputs and outputs are uncompressed.

Configuration

Here is the latest documented configuration file. Key sections:

• downsampling — method (random / random_pct), max_entries, percent, threads, and input_format (fastq / fasta)

Changelog

Version	Description
0.10.0	Migrate to Poetry / pyproject.toml packaging Simplify __init__.py using importlib.metadata Rewrite CLI with rich_click (replaces argparse) Update CI to use setup-micromamba with generate-run-shell Add localrules: pipeline Add tools.txt and environment.yml Refresh README badges and usage examples
0.9.0	Maintenance release
0.8.5	Cope with R1/R2 paired data properly. Improved make file
0.8.4	Add missing MANIFEST to include missing requirements.txt
0.8.3	Comply with new API from sequana_pipetools 0.2.4
0.8.2	Add a –run option to execute the pipeline directly
0.8.1	Fix input and N in the random selection
0.8.0	First release.

Contribute & Code of Conduct

To contribute to this project, please take a look at the Contributing Guidelines first. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.