autoprot streamlines and simplifies proteomics data analysis from preprocessing to visualisation.
Its main features are:
- Works with Pandas dataframes
- Is modularised so that only a required submodule can be loaded for a certain task
- Connects with established R functions for advances bio-statistical analysis
- Supports interactive visualisations made with Plotly
- Generate a new python environment using anaconda or pip.
- Install required Python packages (see requirements.txt) in the environment
- Download or clone autoprot
- If you clone the repository, make sure to include the dependencies as submodules (example below)
git clone --recurse-submodules https://github.com/ag-warscheid/autoprot.git
- If you happen for some reason to forget the submodules, you can still add them later
git submodule update --init --recursive
- Next you need to install R. Please follow the instructions at the R manual and install R to a custom location
- Start autoprot by importing it from any Python console you like. It will generate an autoprot.conf file in the autoprot package directory that you need to edit.
- Insert the path to your Rscript executable that you just installed as value for the R variable
- The RFunctions variable should point the RFunctions.R file from autoprot.
- You can now either try to start using autoprot (it will automatically install required R packages) or manually trigger the install (recommended).
- For this open your R console and start Functions.R with Rscript
C:\Users\User\Documents\R\R-4.1.3\bin\Rscript.exe RFunctions.R
- You can now start with e.g. with the example notebook 01_ap-ms.ipynb provided with autoprot.
- A more detailed description of the installation can be found in the documentation.
Please find the full documentation including function references at https://ag-warscheid.github.io/autoprot/installation.html.
If you want to contribute to the code or found a bug, please feel free to submit an issue or a pull request to https://github.com/ag-warscheid/autoprot.