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https://github.com/sequana/quality_control

A quality control pipeline for illumina data set. This pipeline removes contaminants (e.g. Phix), performs fastqc, adapter cleaning and trimming and checks for contaminants
https://github.com/sequana/quality_control

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A quality control pipeline for illumina data set. This pipeline removes contaminants (e.g. Phix), performs fastqc, adapter cleaning and trimming and checks for contaminants

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.. image:: https://badge.fury.io/py/sequana-quality-control.svg
:target: https://pypi.python.org/pypi/sequana_quality_control

.. image:: http://joss.theoj.org/papers/10.21105/joss.00352/status.svg
:target: http://joss.theoj.org/papers/10.21105/joss.00352
:alt: JOSS (journal of open source software) DOI

.. image:: https://github.com/sequana/quality_control/actions/workflows/main.yml/badge.svg
:target: https://github.com/sequana/quality_control/actions/workflows

This pipeline is not maintained anymore but should be functional. It is a short-read quality control pipeline
from the `Sequana `_ project. We would recommend to use the fastqc, demultiplex,
and multitax pipelines instead.

:Overview: A quality control pipeline for illumina data set. This pipeline removes contaminants (e.g. Phix), performs fastqc, adapter cleaning and trimming and checks for contaminants
:Input: Raw fastq files
:Output: Cleaned fastQ files, remove phix and adapters + taxonomy
:Status: production. **not maintained**. Please use sequana_fastqc and sequana_multitax pipeline instead
: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
~~~~~~~~~~~~

You must install Sequana first::

pip install sequana

Then, just install this package::

pip install sequana_quality_control

Usage
~~~~~

::

sequana_quality_control --help
sequana_quality_control --input-directory DATAPATH

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

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

Or use `sequanix `_ interface.

Requirements
~~~~~~~~~~~~

This pipelines requires the following executable(s):

- fastqc
- bwa
- sambamba
- samtools
- pigz
- cutadapt [or atropos]

.. image:: https://raw.githubusercontent.com/sequana/quality_control/master/sequana_pipelines/quality_control/dag.png

Details
~~~~~~~

This pipeline runs **quality_control** 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
========= ====================================================================
0.11.0 * switch to click, pyproject. remove kraken (see multitax pipeline
instead)
0.10.0 * add missing MANIFEST
0.9.0 * remove design_file for cutadapt to reflect changes in
sequana 0.12.0
* update kraken rules to use a kraken2 version
* Update to use new sequana framework (0.12)
* added CI action
0.8.4 * fix the onsuccess section to reflect changes in sequana 0.9.3
0.8.3 * fix cleaning output files
0.8.2 * fix typo in parameter (-skip-phix-removal --> --skip-phix-removal)
* implement hiearchical kraken analysis. Required major updates of
the sequana kraken rules + general fixes in sequana
0.8.1 uses more sequana tools to handle the options
========= ====================================================================