PROTRIDER is an autoencoder-based method to call protein outliers from mass spectrometry-based proteomics datasets.
For more information see:
PROTRIDER was trained and tested using Python 3.8 on a Linux system. The list of required packages for running PROTRIDER can be found in the file requirements.txt.
Using pip and conda environments We recommend installing and running PROTRIDER on a dedicated conda environment. To create and activate the conda environment run the following commands:
conda create --name protrider_env python=3.8
conda activate protrider_env
More information on conda environments can be found in Conda's user guide.
To install PROTRIDER run the following command inside the root directory:
pip install .
To test the installation run
protrider --help
- Experimental protein intensities as csv or tab file, in which the columns represent samples and the rows represent proteins.
- Optional: sample annotation file containing known covariates to be passed to the model.
An example dataset can be found in this repository.
To run PROTRIDER, a configuration file needs to be provided. This can be adapted from the configuration file provided in this code repo (config.yaml). User options include
out_dir: Path to the directory to store output files.cov_used: List of column names contained in the sample annotation file to be included as known covariates.find_q_method: Method to determine latent space dimension of autoencoder.pval_dist: Distribution (Gaussian or Student's t-test) for P-value calculation.
Run PROTRIDER using the following command:
protrider --config <config_path> --input_intensities <intensities_path> --sample_annotation <sample_anno_path>