sequana-multicov 1.1.1

Installation

sequana_multicov is based on Python3, just install the package as follows:

pip install sequana_multicov --upgrade

Usage

sequana_multicov --help
sequana_multicov --input-directory DATAPATH

By default, this looks for BED file. WARNING. This are BED3 meaning a 3-columns tabulated file like this one:

chr1 1 10
chr1 2 11
...
chr1 N1 10
chr2 1 20
chr2 2 21
...
chr2 N2 20

where the first column stored the chromosome name, the second is the position and the third is the coverage itself. See sequana_coverage documentation for details. If you have BAM files as input, we will do the conversion for you. In such case, use this option:

--input-pattern "*.bam"

The sequana_coverage script creates a directory with the pipeline and its configuration file. You will then need to execute the pipeline:

cd coverage
sh coverage.sh  # for a local run

This launch a snakemake pipeline. If you are familiar with snakemake, you can retrieve the pipeline itself and its configuration files and then execute the pipeline yourself with specific parameters:

snakemake -s multicov.rules -c config.yaml --cores 4 --stats stats.txt

Or use sequanix interface as follows:

sequanix -w analysis -i . -p coverage

Go to the second panel, in Input data and then in Input directory. There, you must modify the pattern (empty field by default meaning search for fastq files) and set the field to either:

*.bed

or:

*.bam

You are ready to go. Save the project and press Run. Once done, open the HTML report.

Requirements

This pipelines requires the following executable(s):

• sequana_coverage from Sequana, which should be installed automatically.

• multiqc

Details

This pipeline runs coverage in parallel on the input BAM files (or BED file).

The coverage tool takes as input a BAM or a BED file. The BED file must have 3 or 4 columns as explained in the standalone application (sequana_coverage) documentation. In short, the first column is the chromosome name, the second column is the position (sorted) and the third column is the coverage (an optional fourth column would contain a coverage signal, which could be high quality coverage for instance).

If you have only BAM files, you can convert them using bioconvert tool or the command:

samtools depth -aa input.bam > output.bed

If you have a CRAM file:

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

For very large BAM/BED files, we recommend to split the BED file by chromosomes. For instance for the chromosome chr1, type:

# samtools index in.bam
samtools depth -aa input.bam -r chr1 in.bam > chr1.bed

The standalone or Snakemake application can also take as input your BAM file and will convert it automatically into a BED file.

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