This is a Python implementation of the package PROGENy for pathway activity prediction from transcriptomics data. In this implementation, PROGENy uses the scanpy framework.
The package can easly be installed using pip
pip install git+https://github.com/saezlab/progeny-py.git
Besides the original paper, there are two additional publication describing expansions of PROGENy usage.
- If you use PROGENy for your research please cite the original publication:
Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. “Perturbation-response genes reveal signaling footprints in cancer gene expression.” Nature Communications: 10.1038/s41467-017-02391-6
- If you use for mouse or you use the expanded version containing 14 pathways, please cite additionally:
Holland CH, Szalai B, Saez-Rodriguez J. "Transfer of regulatory knowledge from human to mouse for functional genomics analysis." Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 2019. DOI: 10.1016/j.bbagrm.2019.194431.
- If you apply PROGENy on single-cell RNA-seq data please cite additionally:
Holland CH, Tanevski J, Perales-Patón J, Gleixner J, Kumar MP, Mereu E, Joughin BA, Stegle O, Lauffenburger DA, Heyn H, Szalai B, Saez-Rodriguez, J. "Robustness and applicability of transcription factor and pathway analysis tools on single-cell RNA-seq data." Genome Biology. 2020. DOI: 10.1186/s13059-020-1949-z.