[![PyPI version](https://badge.fury.io/py/alphastats.svg)](https://badge.fury.io/py/alphastats)
[![codecov](https://codecov.io/gh/MannLabs/alphastats/branch/main/graph/badge.svg?token=HY4A0KKLRI)](https://codecov.io/gh/MannLabs/alphastats)
[![Downloads](https://static.pepy.tech/badge/alphastats)](https://pepy.tech/project/alphastats)
[![Downloads](https://static.pepy.tech/badge/alphastats/week)](https://pepy.tech/project/alphastats)
[![CI](https://github.com/MannLabs/alphapeptstats/actions/workflows/python-package.yml/badge.svg)](https://github.com/MannLabs/alphapeptstats/actions/workflows/python-package.yml)
[![Documentation Status](https://readthedocs.org/projects/alphapeptstats/badge/?version=latest)](https://alphapeptstats.readthedocs.io/en/latest/?badge=latest)
<div align = center>
<img src="https://github.com/MannLabs/alphapeptstats/blob/main/misc/alphastats_workflow.png?raw=true" width="771.4" height="389.2">
</div>
<div align = center>
<br>
<br>
[<kbd> <br> Documentation <br> </kbd>][link]
</div>
<br>
<br>
[link]:https://alphapeptstats.readthedocs.io/en/main/
<div align = center>
<br>
<br>
[<kbd> <br> Streamlit WebApp <br> </kbd>][link_streamlit]
</div>
<br>
<br>
[link_streamlit]:https://mannlabs-alphapeptstats-alphastatsguialphapeptstats-qyzgwd.streamlit.app/
An open-source Python package for downstream mass spectrometry downstream data analysis from the [Mann Group at the University of Copenhagen](https://www.cpr.ku.dk/research/proteomics/mann/).
* [**Citation**](#citation)
* [**Installation**](#installation)
* [**Troubleshooting**](#troubleshooting)
* [**License**](#license)
* [**How to contribute**](#how-to-contribute)
* [**Changelog**](#changelog)
---
## Citation
Publication: [AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics](https://doi.org/10.1093/bioinformatics/btad461)
> **Citation:** <br>
> Krismer, E., Bludau, I., Strauss M. & Mann M. (2023). AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics. Bioinformatics
> https://doi.org/10.1093/bioinformatics/btad461
---
## Installation
AlphaPeptStats can be used as
* python library (pip-installation), or
* Graphical User Interface (either pip-installation or one-click installer).
Further we provide a Dockerimage for the GUI.
### Pip Installation
AlphaStats can be installed in an existing Python 3.8/3.9/3.10 environment with a single `bash` command.
```bash
pip install alphastats
```
In case you want to use the Graphical User Interface, use following command in the command line:
```bash
alphastats gui
```
AlphaStats can be imported as a Python package into any Python script or notebook with the command `import alphastats`.
A brief [Jupyter notebook tutorial](nbs/getting_started.ipynb) on how to use the API is also present in the [nbs folder](nbs).
### One Click Installer
One click Installer for MacOS, Windows and Linux can be found [here](https://github.com/MannLabs/alphapeptstats/releases).
### Docker Image
We provide two Dockerfiles, one for the library and one for the Graphical User Interface.
The Image can be pulled from Dockerhub
```bash
docker pull elenakrismer/alphapeptstats_streamlit
```
---
## GUI
![](https://github.com/MannLabs/alphapeptstats/blob/main/misc/volcano.gif)
---
## Troubleshooting
In case of issues, check out the following:
* [Issues](https://github.com/MannLabs/alphapeptstats/issues): Try a few different search terms to find out if a similar problem has been encountered before
---
## License
AlphaStats was developed by the [Mann Group at the University of Copenhagen](https://www.cpr.ku.dk/research/proteomics/mann/) and is freely available with an [Apache License](LICENSE.txt). External Python packages (available in the [requirements](requirements) folder) have their own licenses, which can be consulted on their respective websites.
---
## How to contribute
If you like this software, you can give us a [star](https://github.com/MannLabs/alphapeptstats/stargazers) to boost our visibility! All direct contributions are also welcome. Feel free to post a new [issue](https://github.com/MannLabs/alphapeptstats/issues) or clone the repository and create a [pull request](https://github.com/MannLabs/alphapeptstats/pulls) with a new branch. For an even more interactive participation, check out the [discussions](https://github.com/MannLabs/alphapeptstats/discussions) and the [the Contributors License Agreement](misc/CLA.md).
---
## Changelog
See the [HISTORY.md](HISTORY.md) for a full overview of the changes made in each version.
---
## FAQ
### How can I resolve the Microsoft visual error message when installing: error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools"?
Please, find a description on how to update required tools [here](https://github.com/MannLabs/alphapeptstats/issues/158).
## How to resolve ERROR:: Could not find a local HDF5 installation. on Mac M1?
Before installing AlphaPeptStats you might need to install pytables first:
````
conda install -c anaconda pytables
````
Raw data
{
"_id": null,
"home_page": "https://github.com/MannLabs/alphastats",
"name": "alphastats",
"maintainer": null,
"docs_url": null,
"requires_python": "<4,>=3.8",
"maintainer_email": null,
"keywords": "bioinformatics, software, mass spectometry",
"author": "Mann Labs",
"author_email": "elena.krismer@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/39/30/859998672a02cb09b62057a1344bc5c38be088d1c39bbdf53eb89e364dd9/alphastats-0.6.9.tar.gz",
"platform": null,
"description": "[![PyPI version](https://badge.fury.io/py/alphastats.svg)](https://badge.fury.io/py/alphastats)\n[![codecov](https://codecov.io/gh/MannLabs/alphastats/branch/main/graph/badge.svg?token=HY4A0KKLRI)](https://codecov.io/gh/MannLabs/alphastats)\n[![Downloads](https://static.pepy.tech/badge/alphastats)](https://pepy.tech/project/alphastats)\n[![Downloads](https://static.pepy.tech/badge/alphastats/week)](https://pepy.tech/project/alphastats)\n[![CI](https://github.com/MannLabs/alphapeptstats/actions/workflows/python-package.yml/badge.svg)](https://github.com/MannLabs/alphapeptstats/actions/workflows/python-package.yml)\n[![Documentation Status](https://readthedocs.org/projects/alphapeptstats/badge/?version=latest)](https://alphapeptstats.readthedocs.io/en/latest/?badge=latest)\n\n\n<div align = center>\n<img src=\"https://github.com/MannLabs/alphapeptstats/blob/main/misc/alphastats_workflow.png?raw=true\" width=\"771.4\" height=\"389.2\">\n</div>\n\n\n<div align = center>\n<br>\n<br>\n\n[<kbd>\u2003<br>\u2003Documentation\u2003<br>\u2003</kbd>][link]\n\n</div>\n\n<br>\n<br>\n\n[link]:https://alphapeptstats.readthedocs.io/en/main/\n\n<div align = center>\n<br>\n<br>\n\n[<kbd>\u2003<br> Streamlit WebApp\u2003<br>\u2003</kbd>][link_streamlit]\n\n</div>\n\n<br>\n<br>\n\n[link_streamlit]:https://mannlabs-alphapeptstats-alphastatsguialphapeptstats-qyzgwd.streamlit.app/\n\nAn open-source Python package for downstream mass spectrometry downstream data analysis from the [Mann Group at the University of Copenhagen](https://www.cpr.ku.dk/research/proteomics/mann/).\n\n\n* [**Citation**](#citation)\n* [**Installation**](#installation)\n* [**Troubleshooting**](#troubleshooting)\n* [**License**](#license)\n* [**How to contribute**](#how-to-contribute)\n* [**Changelog**](#changelog)\n\n---\n## Citation\nPublication: [AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics](https://doi.org/10.1093/bioinformatics/btad461)\n> **Citation:** <br>\n> Krismer, E., Bludau, I., Strauss M. & Mann M. (2023). AlphaPeptStats: an open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics. Bioinformatics \n> https://doi.org/10.1093/bioinformatics/btad461\n\n---\n## Installation\n\nAlphaPeptStats can be used as \n * python library (pip-installation), or \n * Graphical User Interface (either pip-installation or one-click installer). \n \nFurther we provide a Dockerimage for the GUI.\n\n### Pip Installation\n\nAlphaStats can be installed in an existing Python 3.8/3.9/3.10 environment with a single `bash` command. \n\n```bash\npip install alphastats\n```\n\nIn case you want to use the Graphical User Interface, use following command in the command line:\n \n```bash\nalphastats gui\n```\n\nAlphaStats can be imported as a Python package into any Python script or notebook with the command `import alphastats`.\nA brief [Jupyter notebook tutorial](nbs/getting_started.ipynb) on how to use the API is also present in the [nbs folder](nbs).\n\n\n### One Click Installer\n\nOne click Installer for MacOS, Windows and Linux can be found [here](https://github.com/MannLabs/alphapeptstats/releases).\n\n\n### Docker Image\n\nWe provide two Dockerfiles, one for the library and one for the Graphical User Interface.\nThe Image can be pulled from Dockerhub\n\n```bash\ndocker pull elenakrismer/alphapeptstats_streamlit\n```\n\n---\n## GUI\n![](https://github.com/MannLabs/alphapeptstats/blob/main/misc/volcano.gif)\n\n---\n## Troubleshooting\n\nIn case of issues, check out the following:\n\n* [Issues](https://github.com/MannLabs/alphapeptstats/issues): Try a few different search terms to find out if a similar problem has been encountered before\n\n---\n## License\n\nAlphaStats was developed by the [Mann Group at the University of Copenhagen](https://www.cpr.ku.dk/research/proteomics/mann/) and is freely available with an [Apache License](LICENSE.txt). External Python packages (available in the [requirements](requirements) folder) have their own licenses, which can be consulted on their respective websites.\n\n---\n## How to contribute\n\nIf you like this software, you can give us a [star](https://github.com/MannLabs/alphapeptstats/stargazers) to boost our visibility! All direct contributions are also welcome. Feel free to post a new [issue](https://github.com/MannLabs/alphapeptstats/issues) or clone the repository and create a [pull request](https://github.com/MannLabs/alphapeptstats/pulls) with a new branch. For an even more interactive participation, check out the [discussions](https://github.com/MannLabs/alphapeptstats/discussions) and the [the Contributors License Agreement](misc/CLA.md).\n\n---\n## Changelog\n\nSee the [HISTORY.md](HISTORY.md) for a full overview of the changes made in each version.\n\n\n---\n## FAQ\n\n### How can I resolve the Microsoft visual error message when installing: error: Microsoft Visual C++ 14.0 or greater is required. Get it with \"Microsoft C++ Build Tools\"?\nPlease, find a description on how to update required tools [here](https://github.com/MannLabs/alphapeptstats/issues/158).\n\n## How to resolve ERROR:: Could not find a local HDF5 installation. on Mac M1?\n\nBefore installing AlphaPeptStats you might need to install pytables first:\n\n````\nconda install -c anaconda pytables\n````\n",
"bugtrack_url": null,
"license": "Apache",
"summary": "An open-source Python package for automated and scalable statistical analysis of mass spectrometry-based proteomics",
"version": "0.6.9",
"project_urls": {
"GitHub": "https://github.com/MannLabs/alphapeptstats",
"Homepage": "https://github.com/MannLabs/alphastats",
"Mann Labs at MPIB": "https://www.biochem.mpg.de/mann",
"PyPi": "https://pypi.org/project/alphastats/",
"ReadTheDocs": "https://mannlabs.github.io/alphapeptstats/"
},
"split_keywords": [
"bioinformatics",
" software",
" mass spectometry"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "e2512d4cabc2ebd962ca751ea7f0f8f39f8b8aff5ba50cb3aa176b8082b5c262",
"md5": "2ebf6f1c5c4894fa56de3d33e1b3c716",
"sha256": "15085a350d98528754aa695f053aa04340371e42caa74f21fda20e859f7bf167"
},
"downloads": -1,
"filename": "alphastats-0.6.9-py3-none-any.whl",
"has_sig": false,
"md5_digest": "2ebf6f1c5c4894fa56de3d33e1b3c716",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4,>=3.8",
"size": 2861569,
"upload_time": "2024-09-20T13:42:56",
"upload_time_iso_8601": "2024-09-20T13:42:56.496673Z",
"url": "https://files.pythonhosted.org/packages/e2/51/2d4cabc2ebd962ca751ea7f0f8f39f8b8aff5ba50cb3aa176b8082b5c262/alphastats-0.6.9-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "3930859998672a02cb09b62057a1344bc5c38be088d1c39bbdf53eb89e364dd9",
"md5": "bbebd3f19f15f19927eb43dc3005e060",
"sha256": "f1de15931bbfc12f8f5339a536d58cfe8b600280f057cd9a72a2af5418d4d162"
},
"downloads": -1,
"filename": "alphastats-0.6.9.tar.gz",
"has_sig": false,
"md5_digest": "bbebd3f19f15f19927eb43dc3005e060",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4,>=3.8",
"size": 2854252,
"upload_time": "2024-09-20T13:42:58",
"upload_time_iso_8601": "2024-09-20T13:42:58.087323Z",
"url": "https://files.pythonhosted.org/packages/39/30/859998672a02cb09b62057a1344bc5c38be088d1c39bbdf53eb89e364dd9/alphastats-0.6.9.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-09-20 13:42:58",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "MannLabs",
"github_project": "alphastats",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"requirements": [
{
"name": "pandas",
"specs": [
[
"==",
"2.0.2"
]
]
},
{
"name": "scikit-learn",
"specs": [
[
"==",
"1.2.2"
]
]
},
{
"name": "data_cache",
"specs": [
[
">=",
"0.1.6"
]
]
},
{
"name": "plotly",
"specs": [
[
"==",
"5.15.0"
]
]
},
{
"name": "statsmodels",
"specs": [
[
"==",
"0.14.0"
]
]
},
{
"name": "sklearn_pandas",
"specs": [
[
"==",
"2.2.0"
]
]
},
{
"name": "pingouin",
"specs": [
[
"==",
"0.5.3"
]
]
},
{
"name": "scipy",
"specs": [
[
"==",
"1.10.1"
]
]
},
{
"name": "tqdm",
"specs": [
[
">=",
"4.64.0"
]
]
},
{
"name": "diffxpy",
"specs": [
[
"==",
"0.7.4"
]
]
},
{
"name": "anndata",
"specs": [
[
"==",
"0.9.1"
]
]
},
{
"name": "umap-learn",
"specs": [
[
"==",
"0.5.3"
]
]
},
{
"name": "streamlit",
"specs": [
[
"==",
"1.22.0"
]
]
},
{
"name": "tables",
"specs": [
[
"==",
"3.7.0"
]
]
},
{
"name": "numpy",
"specs": [
[
"==",
"1.23.5"
]
]
},
{
"name": "numba",
"specs": [
[
"==",
"0.56.4"
]
]
},
{
"name": "numba-stats",
"specs": [
[
"==",
"0.5.0"
]
]
},
{
"name": "swifter",
"specs": [
[
"==",
"1.2.0"
]
]
},
{
"name": "click",
"specs": [
[
"==",
"8.0.1"
]
]
},
{
"name": "kaleido",
"specs": [
[
"==",
"0.2.1"
]
]
},
{
"name": "combat",
"specs": [
[
"==",
"0.3.3"
]
]
},
{
"name": "xlsxwriter",
"specs": [
[
"==",
"3.1.0"
]
]
},
{
"name": "pyteomics",
"specs": [
[
"==",
"4.6.0"
]
]
},
{
"name": "openpyxl",
"specs": [
[
">=",
"3.0.10"
]
]
},
{
"name": "nbformat",
"specs": [
[
">=",
"5.0"
]
]
}
],
"lcname": "alphastats"
}