DOI: 10.18129/B9.bioc.DepInfeR    

This is the development version of DepInfeR; for the stable release version, see DepInfeR.

Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling

Bioconductor version: Development (3.16)

DepInfeR integrates two experimentally accessible input data matrices: the drug sensitivity profiles of cancer cell lines or primary tumors ex-vivo (X), and the drug affinities of a set of proteins (Y), to infer a matrix of molecular protein dependencies of the cancers (ß). DepInfeR deconvolutes the protein inhibition effect on the viability phenotype by using regularized multivariate linear regression. It assigns a “dependence coefficient” to each protein and each sample, and therefore could be used to gain a causal and accurate understanding of functional consequences of genomic aberrations in a heterogeneous disease, as well as to guide the choice of pharmacological intervention for a specific cancer type, sub-type, or an individual patient. For more information, please read out preprint on bioRxiv:

Author: Junyan Lu [aut, cre] , Alina Batzilla [aut]

Maintainer: Junyan Lu <jylu1118 at>

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biocViews FunctionalGenomics, Pharmacogenetics, Pharmacogenomics, Regression, Software
Version 1.1.0
In Bioconductor since BioC 3.15 (R-4.2) (< 6 months)
License GPL-3
Depends R (>= 4.2.0)
Imports matrixStats, glmnet, stats, BiocParallel
Suggests testthat (>= 3.0.0), knitr, rmarkdown, dplyr, tidyr, tibble, ggplot2, missForest, pheatmap, RColorBrewer, ggrepel, ggbeeswarm
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