HTSeq

DEVS: https://github.com/htseq/htseq

CITATION (please cite this new paper!): Putri et al. Analysing high-throughput sequencing data in Python with HTSeq 2.0. Bioinformatics, btac166, https://doi.org/10.1093/bioinformatics/btac166 (2022).

A Python library to facilitate programmatic analysis of data from high-throughput sequencing (HTS) experiments. A popular component of HTSeq is htseq-count, a script to quantify gene expression in bulk and single-cell RNA-Seq and similar experiments.

Requirements

To use HTSeq you need:

Python >= 3.7 (note: Python 2.7 support has been dropped)
numpy
pysam

To manipulate BigWig files, you also need:

pyBigWig

To run the htseq-qa script, you also need:

matplotlib

To run htseq-count and htseq-count-barcodes with custom output formats for the counts table, you need:

mtx file: scipy
h5ad file: anndata
loom file: loompy

Both Linux and OSX are supported and binaries are provided on Pypi. We would like to support Windows but currently lack the expertise to do so. If you would like to take on the Windows release and maintenance, please open an issue and we'll try to help.

A source package which should not require Cython nor SWIG is also provided on Pypi.

To develop HTSeq you will also need:

Cython >=0.29.5
SWIG >=3.0.8

Installation

PIP

To install directly from PyPI:

pip install HTSeq

To install a specific version:

pip install 'HTSeq==0.13.5'

If this fails, please install all dependencies first:

pip install matplotlib
pip install Cython
pip install pysam
pip install HTSeq

setup.py (distutils/setuptools)

Install the dependencies with your favourite tool (pip, conda, etc.).

To install HTSeq itself, run:

python setup.py build install

Testing

To test locally, run

./test.sh

To test htseq-count alone, run it with the -o option.

A virtual environment is created in the .venv folder and HTSeq is installed inside it, including all modules and scripts.

Authors

2021-: Givanna Putri
2016-: Fabio Zanini @ https://fabilab.org
2010-2015: Simon Anders, Wolfgang Huber