sequana-slicer 0.1.0

SLicer detects splice leader sequences from long-read data using motif detection and soft-clip analysis.

This is the slicer pipeline from the Sequana project

Overview:

Detects splice leader sequences from long-read (PacBio) data using motif-based read filtering, soft-clip analysis, sequence clustering, and multiple sequence alignment.

Input:

Long-read FASTQ files (PacBio) and a reference genome FASTA file.

Output:

Clustered and aligned soft-clipped sequences (FASTA), per-sample HTML reports, and a merged CSV statistics file.

Status:

beta

Citation:

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

Installation

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

pip install sequana_slicer --upgrade

You will need third-party tools. Please see below for details.

Usage

sequana_slicer --help
sequana_slicer --input-directory DATAPATH --reference-file reference.fasta

This creates a directory with the pipeline and configuration file. You will then need to execute the pipeline:

cd slicer
sh slicer.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 slicer.rules -c config.yaml --cores 4 --stats stats.txt

Or use sequanix interface.

Usage with apptainer / singularity

With Apptainer, initiate the working directory as follows:

sequana_slicer --input-directory DATAPATH --reference-file reference.fasta \
    --apptainer-prefix ~/.sequana/apptainers

Images are downloaded in the working directory but you can store them in a shared directory to avoid re-downloading them (recommended for repeated use):

sequana_slicer --input-directory DATAPATH --reference-file reference.fasta \
    --apptainer-prefix ~/.sequana/apptainers

and then:

cd slicer
sh slicer.sh

if you decide to use snakemake manually, do not forget to add apptainer options:

snakemake -s slicer.rules -c config.yaml --cores 4 --stats stats.txt \
    --apptainer-prefix ~/.sequana/apptainers \
    --apptainer-args "-B /home:/home"

By default, the home is already set for you. Additional binding path can be set using environment variables e.g.:

export APPTAINER_BINDPATH=" -B /pasteur"

Requirements

This pipelines requires the following executable(s):

• seqkit

• minimap2

• samtools

• cd-hit-est

• mafft

• graphviz

These tools are available as Apptainer/Singularity containers (see config.yaml for container URLs).

Details

This pipeline runs slicer in parallel on the input fastq files (paired or not). A brief sequana summary report is also produced.

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

Version	Description
0.0.1	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.