sequana-multicov 1.2.0

Installation

If you already have all requirements, install the package using pip:

pip install sequana_multicov --upgrade

Usage

Scan BED files in a directory and set up the pipeline (replace DATAPATH with your input directory):

sequana_multicov --input-directory DATAPATH

To provide a reference FASTA file for GC content plots:

sequana_multicov --input-directory DATAPATH --reference-file genome.fa

To provide a GenBank annotation file for event annotation:

sequana_multicov --input-directory DATAPATH --annotation-file genome.gbk

This creates a multicov/ directory with the pipeline and configuration file. Execute the pipeline locally:

cd multicov
sh multicov.sh

If you are familiar with Snakemake, you can also run the pipeline directly:

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

See .sequana/profile/config.yaml to tune Snakemake behaviour (cores, cluster settings, etc.).

Usage with apptainer

With apptainer, initiate the working directory as follows:

sequana_multicov --input-directory DATAPATH --use-apptainer

Images are downloaded in the working directory but you can store them in a shared location:

sequana_multicov --input-directory DATAPATH --use-apptainer --apptainer-prefix ~/.sequana/apptainers

and then:

cd multicov
sh multicov.sh

Input format

BED files must have 3 or 4 tab-separated columns:

chr1    1    10
chr1    2    11
...
chr2    1    20
chr2    2    21
...

where the first column is the chromosome/contig name, the second is the position (1-based, sorted), and the third is the coverage depth. An optional fourth column may contain a filtered coverage signal (shown in reports but not used in the analysis).

If you only have BAM files, convert them with:

samtools depth -aa input.bam > output.bed

For a specific chromosome only:

samtools depth -aa -r chr1 input.bam > chr1.bed

For CRAM files, convert to BAM first:

samtools view -@ 4 -T reference.fa -b -o out.bam in.cram

Requirements

This pipeline requires the following executables:

• sequana_coverage — from the Sequana package (installed automatically)

• multiqc — aggregated HTML report across samples

Install all dependencies at once:

mamba env create -f environment.yml

Details

This pipeline runs sequana_coverage in parallel across all input BED files. For each sample it produces a standalone HTML report with:

• coverage plots and running-median normalisation

• ROI (region of interest) detection using z-score thresholds

• CNV clustering

• GC content overlay (when a reference FASTA is provided)

• Event annotation (when a GenBank file is provided)

On success, a summary.html is generated listing all samples with direct links to their individual reports, plus a MultiQC report aggregating key statistics across samples.

For very large genomes the --binning and --chunksize options can be used to reduce memory usage.

Rules and configuration details

Here is the latest documented configuration file to be used with the pipeline. Each rule used in the pipeline may have a section in the configuration file.

Changelog

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.