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 our paper: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010438
Package details |
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Bioconductor views | FunctionalGenomics Pharmacogenetics Pharmacogenomics Regression Software |
Maintainer | |
License | GPL-3 |
Version | 0.99.9 |
Package repository | View on GitHub |
Installation |
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