AlphaRaw
================
[](https://github.com/MannLabs/alpharaw/actions/workflows/pip_installation.yml)
[](https://github.com/MannLabs/alpharaw/actions/workflows/publish_and_release.yml)
[](https://pypi.org/project/alpharaw)
[](https://pypi.org/project/alpharaw)
[](https://alpharaw.readthedocs.io/en/latest/?badge=latest)
## About
An open-source Python package of the AlphaPept ecosystem from the [Mann
Labs at the Max Planck Institute of
Biochemistry](https://www.biochem.mpg.de/mann) to unify raw MS data
accession and storage. To enable all hyperlinks in this document, please
view it at [GitHub](https://github.com/MannLabs/alpharaw).
- [**About**](#about)
- [**License**](#license)
- [**Installation**](#installation)
- [**Pip installer**](#pip)
- [**Developer installer**](#developer)
- [**Usage**](#usage)
- [**Python and jupyter notebooks**](#python-and-jupyter-notebooks)
- [**Troubleshooting**](#troubleshooting)
- [**Citations**](#citations)
- [**How to contribute**](#how-to-contribute)
- [**Changelog**](#changelog)
------------------------------------------------------------------------
## License
AlphaRaw was developed by the [Mann Labs at the Max Planck Institute of
Biochemistry](https://www.biochem.mpg.de/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.
------------------------------------------------------------------------
## Installation
Pythonnet must be installed to access Thermo or Sciex raw data.
#### For Windows
Pythonnet will be automatically installed via pip.
#### For Linux (or MacOS without M1/M2/M3/..., not tested yet)
1. `conda install mono`.
2. Install pythonnet with `pip install pythonnet`.
If `conda install mono` does not work, we can install Mono from mono-project website [Mono
Linux](https://www.mono-project.com/download/stable/#download-lin).
NOTE, the installed mono version should be at least 6.10, which
requires you to add the ppa to your trusted sources!
#### For MacOS including M1/M2 platform
1. Install [brew](https://brew.sh).
2. Install mono: `brew install mono`.
3. If the pseudo mono folder `/Library/Frameworks/Mono.framework/Versions` does not exist, create it by running `sudo mkdir -p /Library/Frameworks/Mono.framework/Versions`.
4. Link homebrew mono to pseudo mono folder: `sudo ln -s /opt/homebrew/Cellar/mono/6.12.0.182 /Library/Frameworks/Mono.framework/Versions/Current`. Here, `6.12.0.182` is the brew-installed mono version, please check your installed version. Navigate to `/Library/Frameworks/Mono.framework/Versions` and run `ls -l` to verify that the link `Current` points to `/opt/homebrew/Cellar/mono/6.12.0.182`. If `Current` points to a different installation and/or `/opt/homebrew/Cellar/mono/6.12.0.182` is referenced by a different link, delete the corresponding links and run `sudo ln -s /opt/homebrew/Cellar/mono/6.12.0.182 Current`.
5. Install pythonnet: `pip install pythonnet`.
------------------------------------------------------------------------
AlphaRaw can be installed and used on all major operating systems
(Windows, macOS and Linux). There are three different types of
installation possible:
- [**Pip installer:**](#pip) Choose this installation if you want to use
AlphaRaw as a Python package in an existing Python 3.8 environment
(e.g. a Jupyter notebook).
- [**Developer installer:**](#developer) Choose this installation if you
are familiar with CLI tools, [conda](https://docs.conda.io/en/latest/)
and Python. This installation allows access to all available features
of AlphaRaw and even allows to modify its source code directly.
Generally, the developer version of AlphaRaw outperforms the
precompiled versions which makes this the installation of choice for
high-throughput experiments.
### Pip
AlphaRaw can be installed in an existing Python 3.8 environment with a
single `bash` command. *This `bash` command can also be run directly
from within a Jupyter notebook by prepending it with a `!`*:
``` bash
pip install alpharaw
```
Installing AlphaRaw like this avoids conflicts when integrating it in
other tools, as this does not enforce strict versioning of dependancies.
However, if new versions of dependancies are released, they are not
guaranteed to be fully compatible with AlphaRaw. While this should only
occur in rare cases where dependencies are not backwards compatible, you
can always force AlphaRaw to use dependancy versions which are known to
be compatible with:
``` bash
pip install "alpharaw[stable]"
```
NOTE: You might need to run `pip install pip --upgrade` before installing
AlphaRaw like this. Also note the double quotes `"`.
For those who are really adventurous, it is also possible to directly
install any branch (e.g. `@development`) with any extras
(e.g. `#egg=alpharaw[stable,development-stable]`) from GitHub with e.g.
``` bash
pip install "git+https://github.com/MannLabs/alpharaw.git@development#egg=alpharaw[stable,development-stable]"
```
### Developer
AlphaRaw can also be installed in editable (i.e. developer) mode with a
few `bash` commands. This allows to fully customize the software and
even modify the source code to your specific needs. When an editable
Python package is installed, its source code is stored in a transparent
location of your choice. While optional, it is advised to first (create
and) navigate to e.g. a general software folder:
``` bash
mkdir ~/folder/where/to/install/software
cd ~/folder/where/to/install/software
```
***The following commands assume you do not perform any additional `cd`
commands anymore***.
Next, download the AlphaRaw repository from GitHub either directly or
with a `git` command. This creates a new AlphaRaw subfolder in your
current directory.
``` bash
git clone https://github.com/MannLabs/alpharaw.git
```
For any Python package, it is highly recommended to use a separate
[conda virtual environment](https://docs.conda.io/en/latest/), as
otherwise *dependancy conflicts can occur with already existing
packages*.
``` bash
conda create --name alpharaw python=3.9 -y
conda activate alpharaw
```
Finally, AlphaRaw and all its [dependancies](requirements) need to be
installed. To take advantage of all features and allow development (with
the `-e` flag), this is best done by also installing the [development
dependencies](requirements/requirements_development.txt) instead of only
the [core dependencies](requirements/requirements.txt):
``` bash
pip install -e "./alpharaw[development]"
```
By default this installs loose dependancies (no explicit versioning),
although it is also possible to use stable dependencies
(e.g. `pip install -e "./alpharaw[stable,development-stable]"`).
***By using the editable flag `-e`, all modifications to the [AlphaRaw
source code folder](alpharaw) are directly reflected when running
AlphaRaw. Note that the AlphaRaw folder cannot be moved and/or renamed
if an editable version is installed.***
------------------------------------------------------------------------
## Usage
- [**Python**](#python-and-jupyter-notebooks)
NOTE: The first time you use a fresh installation of AlphaRaw, it is
often quite slow because some functions might still need compilation on
your local operating system and architecture. Subsequent use should be a
lot faster.
### Python and Jupyter notebooks
AlphaRaw can be imported as a Python package into any Python script or
notebook with the command `import alpharaw`.
A brief [Jupyter notebook tutorial](nbs/tutorial.ipynb) on how to use
the API is also present in the [nbs folder](nbs).
------------------------------------------------------------------------
## Troubleshooting
In case of issues, check out the following:
- [Issues](https://github.com/MannLabs/alpharaw/issues): Try a few
different search terms to find out if a similar problem has been
encountered before
- [Discussions](https://github.com/MannLabs/alpharaw/discussions): Check
if your problem or feature requests has been discussed before.
------------------------------------------------------------------------
## Citations
There are currently no plans to draft a manuscript.
------------------------------------------------------------------------
## How to contribute
If you like this software, you can give us a
[star](https://github.com/MannLabs/alpharaw/stargazers) to boost our
visibility! All direct contributions are also welcome. Feel free to post
a new [issue](https://github.com/MannLabs/alpharaw/issues) or clone the
repository and create a [pull
request](https://github.com/MannLabs/alpharaw/pulls) with a new branch.
For an even more interactive participation, check out the
[discussions](https://github.com/MannLabs/alpharaw/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.
Raw data
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"description": "AlphaRaw\n================\n\n[](https://github.com/MannLabs/alpharaw/actions/workflows/pip_installation.yml)\n[](https://github.com/MannLabs/alpharaw/actions/workflows/publish_and_release.yml)\n[](https://pypi.org/project/alpharaw)\n[](https://pypi.org/project/alpharaw)\n\n[](https://alpharaw.readthedocs.io/en/latest/?badge=latest)\n\n## About\n\nAn open-source Python package of the AlphaPept ecosystem from the [Mann\nLabs at the Max Planck Institute of\nBiochemistry](https://www.biochem.mpg.de/mann) to unify raw MS data\naccession and storage. To enable all hyperlinks in this document, please\nview it at [GitHub](https://github.com/MannLabs/alpharaw).\n\n- [**About**](#about)\n- [**License**](#license)\n- [**Installation**](#installation)\n - [**Pip installer**](#pip)\n - [**Developer installer**](#developer)\n- [**Usage**](#usage)\n - [**Python and jupyter notebooks**](#python-and-jupyter-notebooks)\n- [**Troubleshooting**](#troubleshooting)\n- [**Citations**](#citations)\n- [**How to contribute**](#how-to-contribute)\n- [**Changelog**](#changelog)\n\n------------------------------------------------------------------------\n\n## License\n\nAlphaRaw was developed by the [Mann Labs at the Max Planck Institute of\nBiochemistry](https://www.biochem.mpg.de/mann) and is freely available\nwith an [Apache License](LICENSE.txt). External Python packages\n(available in the [requirements](requirements) folder) have their own\nlicenses, which can be consulted on their respective websites.\n\n------------------------------------------------------------------------\n\n## Installation\n\nPythonnet must be installed to access Thermo or Sciex raw data.\n\n#### For Windows\n\nPythonnet will be automatically installed via pip.\n\n#### For Linux (or MacOS without M1/M2/M3/..., not tested yet)\n\n1. `conda install mono`.\n2. Install pythonnet with `pip install pythonnet`.\n\nIf `conda install mono` does not work, we can install Mono from mono-project website [Mono\nLinux](https://www.mono-project.com/download/stable/#download-lin).\nNOTE, the installed mono version should be at least 6.10, which\nrequires you to add the ppa to your trusted sources!\n\n#### For MacOS including M1/M2 platform\n\n1. Install [brew](https://brew.sh).\n2. Install mono: `brew install mono`.\n3. If the pseudo mono folder `/Library/Frameworks/Mono.framework/Versions` does not exist, create it by running `sudo mkdir -p /Library/Frameworks/Mono.framework/Versions`.\n4. Link homebrew mono to pseudo mono folder: `sudo ln -s /opt/homebrew/Cellar/mono/6.12.0.182 /Library/Frameworks/Mono.framework/Versions/Current`. Here, `6.12.0.182` is the brew-installed mono version, please check your installed version. Navigate to `/Library/Frameworks/Mono.framework/Versions` and run `ls -l` to verify that the link `Current` points to `/opt/homebrew/Cellar/mono/6.12.0.182`. If `Current` points to a different installation and/or `/opt/homebrew/Cellar/mono/6.12.0.182` is referenced by a different link, delete the corresponding links and run `sudo ln -s /opt/homebrew/Cellar/mono/6.12.0.182 Current`. \n5. Install pythonnet: `pip install pythonnet`.\n\n------------------------------------------------------------------------\n\nAlphaRaw can be installed and used on all major operating systems\n(Windows, macOS and Linux). There are three different types of\ninstallation possible:\n\n- [**Pip installer:**](#pip) Choose this installation if you want to use\n AlphaRaw as a Python package in an existing Python 3.8 environment\n (e.g.\u00a0a Jupyter notebook).\n- [**Developer installer:**](#developer) Choose this installation if you\n are familiar with CLI tools, [conda](https://docs.conda.io/en/latest/)\n and Python. This installation allows access to all available features\n of AlphaRaw and even allows to modify its source code directly.\n Generally, the developer version of AlphaRaw outperforms the\n precompiled versions which makes this the installation of choice for\n high-throughput experiments.\n\n### Pip\n\nAlphaRaw can be installed in an existing Python 3.8 environment with a\nsingle `bash` command. *This `bash` command can also be run directly\nfrom within a Jupyter notebook by prepending it with a `!`*:\n\n``` bash\npip install alpharaw\n```\n\nInstalling AlphaRaw like this avoids conflicts when integrating it in\nother tools, as this does not enforce strict versioning of dependancies.\nHowever, if new versions of dependancies are released, they are not\nguaranteed to be fully compatible with AlphaRaw. While this should only\noccur in rare cases where dependencies are not backwards compatible, you\ncan always force AlphaRaw to use dependancy versions which are known to\nbe compatible with:\n\n``` bash\npip install \"alpharaw[stable]\"\n```\n\nNOTE: You might need to run `pip install pip --upgrade` before installing\nAlphaRaw like this. Also note the double quotes `\"`.\n\nFor those who are really adventurous, it is also possible to directly\ninstall any branch (e.g.\u00a0`@development`) with any extras\n(e.g.\u00a0`#egg=alpharaw[stable,development-stable]`) from GitHub with e.g.\n\n``` bash\npip install \"git+https://github.com/MannLabs/alpharaw.git@development#egg=alpharaw[stable,development-stable]\"\n```\n\n### Developer\n\nAlphaRaw can also be installed in editable (i.e.\u00a0developer) mode with a\nfew `bash` commands. This allows to fully customize the software and\neven modify the source code to your specific needs. When an editable\nPython package is installed, its source code is stored in a transparent\nlocation of your choice. While optional, it is advised to first (create\nand) navigate to e.g.\u00a0a general software folder:\n\n``` bash\nmkdir ~/folder/where/to/install/software\ncd ~/folder/where/to/install/software\n```\n\n***The following commands assume you do not perform any additional `cd`\ncommands anymore***.\n\nNext, download the AlphaRaw repository from GitHub either directly or\nwith a `git` command. This creates a new AlphaRaw subfolder in your\ncurrent directory.\n\n``` bash\ngit clone https://github.com/MannLabs/alpharaw.git\n```\n\nFor any Python package, it is highly recommended to use a separate\n[conda virtual environment](https://docs.conda.io/en/latest/), as\notherwise *dependancy conflicts can occur with already existing\npackages*.\n\n``` bash\nconda create --name alpharaw python=3.9 -y\nconda activate alpharaw\n```\n\nFinally, AlphaRaw and all its [dependancies](requirements) need to be\ninstalled. To take advantage of all features and allow development (with\nthe `-e` flag), this is best done by also installing the [development\ndependencies](requirements/requirements_development.txt) instead of only\nthe [core dependencies](requirements/requirements.txt):\n\n``` bash\npip install -e \"./alpharaw[development]\"\n```\n\nBy default this installs loose dependancies (no explicit versioning),\nalthough it is also possible to use stable dependencies\n(e.g.\u00a0`pip install -e \"./alpharaw[stable,development-stable]\"`).\n\n***By using the editable flag `-e`, all modifications to the [AlphaRaw\nsource code folder](alpharaw) are directly reflected when running\nAlphaRaw. Note that the AlphaRaw folder cannot be moved and/or renamed\nif an editable version is installed.***\n\n------------------------------------------------------------------------\n\n## Usage\n\n- [**Python**](#python-and-jupyter-notebooks)\n\nNOTE: The first time you use a fresh installation of AlphaRaw, it is\noften quite slow because some functions might still need compilation on\nyour local operating system and architecture. Subsequent use should be a\nlot faster.\n\n### Python and Jupyter notebooks\n\nAlphaRaw can be imported as a Python package into any Python script or\nnotebook with the command `import alpharaw`.\n\nA brief [Jupyter notebook tutorial](nbs/tutorial.ipynb) on how to use\nthe API is also present in the [nbs folder](nbs).\n\n------------------------------------------------------------------------\n\n## Troubleshooting\n\nIn case of issues, check out the following:\n\n- [Issues](https://github.com/MannLabs/alpharaw/issues): Try a few\n different search terms to find out if a similar problem has been\n encountered before\n- [Discussions](https://github.com/MannLabs/alpharaw/discussions): Check\n if your problem or feature requests has been discussed before.\n\n------------------------------------------------------------------------\n\n## Citations\n\nThere are currently no plans to draft a manuscript.\n\n------------------------------------------------------------------------\n\n## How to contribute\n\nIf you like this software, you can give us a\n[star](https://github.com/MannLabs/alpharaw/stargazers) to boost our\nvisibility! All direct contributions are also welcome. Feel free to post\na new [issue](https://github.com/MannLabs/alpharaw/issues) or clone the\nrepository and create a [pull\nrequest](https://github.com/MannLabs/alpharaw/pulls) with a new branch.\nFor an even more interactive participation, check out the\n[discussions](https://github.com/MannLabs/alpharaw/discussions) and the\n[the Contributors License Agreement](misc/CLA.md).\n\n------------------------------------------------------------------------\n\n## Changelog\n\nSee the [HISTORY.md](HISTORY.md) for a full overview of the changes made\nin each version.\n",
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