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# PROGENy: Pathway RespOnsive GENes for activity inference <img src="man/figures/tool_logo.png" align="right" width="120" /> <!-- badges: start --> ![GitHub]( <!-- badges: end --> ## Overview PROGENy is resource that leverages a large compendium of publicly available signaling perturbation experiments to yield a common core of pathway responsive genes for human and mouse. These, coupled with any statistical method, can be used to infer pathway activities from bulk or single-cell transcriptomics. This is an R package for storing the pathway signatures. To infer pathway activities, please check out [decoupleR](, available in [R]( or [python]( ## Installation Progeny is available in [Bioconductor]( In addition, one can install the development version from the Github repository: ```r ## To install the package from Bioconductor if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("progeny") ## To install the development version from the Github repo: devtools::install_github("saezlab/progeny") ``` ## Updates Since the original release, we have implemented some extensions in PROGENy: 1. **Extension to mouse**: Originally PROGENy was developed for the application to human data. In a benchmark study we showed that PROGENy is also applicable to mouse data, as described in [Holland et al., 2019]( Accordingly, we included new parameters to run mouse version of PROGENy by transforming the human genes to their mouse orthologs. 2. **Expanding Pathway Collection**: We expanded human and mouse PROGENy with the pathways Androgen, Estrogen and WNT. 3. **Extension to single-cell RNA-seq data**: We showed that PROGENy can be applied to scRNA-seq data, as described in [Holland et al., 2020]( ## Citation > Schubert M, Klinger B, Klünemann M, Sieber A, Uhlitz F, Sauer S, Garnett MJ, Blüthgen N, Saez-Rodriguez J. 2018. Perturbation-response genes reveal signaling footprints in cancer gene expression. _Nature Communications_: [10.1038/s41467-017-02391-6](