DEVS: https://github.com/htseq/htseq
DOCS: https://htseq.readthedocs.io
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.
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
To install directly from PyPI:
pip install HTSeq
To install a specific version:
pip install 'HTSeq==2.0.0'
If this fails, please install all dependencies first:
pip install matplotlib pip install Cython pip install pysam pip install HTSeqsetup.py (distutils/setuptools)
Install the dependencies with your favourite tool (pip
, conda
, etc.).
To install HTSeq
itself, run:
python setup.py build installTesting
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.
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