| Name | HTSeq JSON |
| Version |
2.0.5
JSON |
| download |
| home_page | https://github.com/htseq |
| Summary | A framework to process and analyze data from high-throughput sequencing (HTS) assays |
| upload_time | 2023-12-13 05:01:40 |
| maintainer | Fabio Zanini |
| docs_url | None |
| author | Simon Anders, Fabio Zanini |
| requires_python | |
| license | GPL3 |
| keywords |
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
[](https://htseq.readthedocs.io)
# 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](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:
```bash
pip install HTSeq
```
To install a specific version:
```bash
pip install 'HTSeq==2.0.0'
```
If this fails, please install all dependencies first:
```bash
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:
```bash
python setup.py build install
```
## Testing
To test locally, run
```bash
./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 ([ghar1821](https://github.com/ghar1821))
- 2016-: Fabio Zanini ([iosonofabio](https://github.com/iosonofabio))@ https://fabilab.org
- 2010-2015: Simon Anders ([simon-anders](https://github.com/simon-anders)), Wolfgang Huber
Raw data
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"description": "\n[](https://htseq.readthedocs.io)\n\n# HTSeq\n**DEVS**: https://github.com/htseq/htseq\n\n**DOCS**: https://htseq.readthedocs.io\n\n**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](https://doi.org/10.1093/bioinformatics/btac166) (2022).\n\nA Python library to facilitate programmatic analysis of data\nfrom high-throughput sequencing (HTS) experiments. A popular component of ``HTSeq``\nis ``htseq-count``, a script to quantify gene expression in bulk and single-cell RNA-Seq\nand similar experiments.\n\n## Requirements\n\nTo use ``HTSeq`` you need:\n\n- ``Python >= 3.7`` (**note**: ``Python 2.7`` support has been dropped)\n- ``numpy``\n- ``pysam``\n\nTo manipulate BigWig files, you also need:\n\n- ``pyBigWig``\n\nTo run the ``htseq-qa`` script, you also need:\n\n- ``matplotlib``\n\nTo run ``htseq-count`` and ``htseq-count-barcodes`` with custom output formats for the counts table, you need:\n\n- ``mtx`` file: ``scipy``\n- ``h5ad`` file: ``anndata``\n- ``loom`` file: ``loompy``\n\nBoth **Linux** and **OSX** are supported and binaries are provided on Pypi. We\nwould like to support **Windows** but currently lack the expertise to do so. If\nyou would like to take on the Windows release and maintenance, please open an\nissue and we'll try to help.\n\nA source package which should not require ``Cython`` nor ``SWIG`` is also\nprovided on Pypi.\n\nTo **develop** `HTSeq` you will **also** need:\n\n- ``Cython >=0.29.5``\n- ``SWIG >=3.0.8``\n\n## Installation\n\n### PIP\n\nTo install directly from PyPI:\n\n```bash\npip install HTSeq\n```\n\nTo install a specific version:\n\n```bash\npip install 'HTSeq==2.0.0'\n```\n\nIf this fails, please install all dependencies first:\n\n```bash\npip install matplotlib\npip install Cython\npip install pysam\npip install HTSeq\n```\n\n### setup.py (distutils/setuptools)\n\nInstall the dependencies with your favourite tool (``pip``, ``conda``,\netc.).\n\nTo install ``HTSeq`` itself, run:\n\n```bash\npython setup.py build install\n```\n\n## Testing\nTo test locally, run\n\n```bash\n./test.sh\n```\n\nTo test `htseq-count` alone, run it with the `-o` option.\n\nA virtual environment is created in the `.venv` folder and `HTSeq` is installed inside it, including all modules and scripts.\n\n## Authors\n- 2021-: Givanna Putri ([ghar1821](https://github.com/ghar1821))\n- 2016-: Fabio Zanini ([iosonofabio](https://github.com/iosonofabio))@ https://fabilab.org\n- 2010-2015: Simon Anders ([simon-anders](https://github.com/simon-anders)), Wolfgang Huber\n",
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