Skip to main content

A framework to process and analyze data from high-throughput sequencing (HTS) assays

Project description

CI Documentation Status

HTSeq

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.

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==2.0.0'

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

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

HTSeq-2.0.3.tar.gz (394.2 kB view details)

Uploaded Source

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

HTSeq-2.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

HTSeq-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl (328.4 kB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

HTSeq-2.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.9 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

HTSeq-2.0.3-cp39-cp39-macosx_10_9_x86_64.whl (332.1 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

HTSeq-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.0 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

HTSeq-2.0.3-cp38-cp38-macosx_10_9_x86_64.whl (357.6 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

HTSeq-2.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.17+ x86-64

HTSeq-2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl (351.1 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file HTSeq-2.0.3.tar.gz.

File metadata

  • Download URL: HTSeq-2.0.3.tar.gz
  • Upload date:
  • Size: 394.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.16

File hashes

Hashes for HTSeq-2.0.3.tar.gz
Algorithm Hash digest
SHA256 c7e7eb29bdc44e80d2d68e3599fa8a8f1d9d6475624dcf1b9644285a8a9c0fac
MD5 d5aff2bd59c349f71f0513da7ba739ef
BLAKE2b-256 836105ce20ed21cedf9c31a0bc20cdffb66012e6ac202609ea1207322895c301

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 073f1243e54e902cfe2ca02655946803c506b496792a72e1784402572889c80a
MD5 c41443c28c2f1f75fd20357c7153f161
BLAKE2b-256 99e06c7785f7e8672a4724acff663d5a31a7706844c067f897a72243eb4d74f8

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 03972ffc34034c8cbdf5587c9a21e5770a12855479807c7cfe54fe20023c095f
MD5 d3f82b5c73a5bfecde01198723dca2b6
BLAKE2b-256 1a393e21fba5d5c28de89cc3d70cc75d855e618f36fa6e0ac0556b20892069cf

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 0c73bccacafee1407ad8c87518af71918593f726279e09f11eefe1d6210ec3bf
MD5 aff1a9ebf32991d09d575b61e3d9f44b
BLAKE2b-256 a3c68b144f72de864489b1d6312c2e297315f5f66ae1ed9ef8dc0812fdece948

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 0affcc9f3881bd17725f76a1525f723c58b9ea359009cc0b4b2db1f731f82ed2
MD5 2bbc481e7d8c2ec7aade296213dcfb55
BLAKE2b-256 d9c1d36bee0edfa32f107fd28313400e35d7216e29d103367eb06c4e79e09c26

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1446f538bcc305859e92b0fc362f5dbe9f7ffe7f495389496fb89f52d52f823f
MD5 5ed6066c4d7dd23fb2001689def82fe8
BLAKE2b-256 4270f69a1e7844ada1b3e8a8b77e0cf337aaa3cc11411db3f65754f68e610f0c

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 5865e07d96abfdd36702171001ece846454f764671357b81702bb1bf082b33a3
MD5 f4b9e530e31ad92f27c758eb488dbf9e
BLAKE2b-256 db6b66aff9c9499850374acb4bab61929e8da65808237f9e5b42dd3038f0c764

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fd6e92a4c16898fb9c9c17fd7a93e0aefe0a0be9c0992175b38fb139c76d3cb2
MD5 d49866ad1d6b7412b7ded6fb367e403c
BLAKE2b-256 60ad00951b2626512a9064a04e0e5f9ae1352cdae0d3acee1482ca45d789136b

See more details on using hashes here.

File details

Details for the file HTSeq-2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for HTSeq-2.0.3-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 700a0453aafd4a03171b2161e7ef1d14d54a77d424f5027ce1ecad0756b04a81
MD5 5ba4b54f94cad238a0e56f93a584180c
BLAKE2b-256 aede17fc86369d1d1891289608ef873a60d19946548b4998d0cadaa6dca421ae

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page