oncoPredict: Drug and Biomarker Discovery

Bridges in vitro drug screening with in vivo drug and biomarker discovery. Specifically, predicts in vivo or cancer patient drug response and biomarkers to enrich for response from cell line screening data. Builds model using ridge regression, and enables biomarker discovery by imputing drug response in large cancer molecular datasets. It also enables drug specific biomarker identification by correcting for general level of drug sensitivity shared among the population.

Version: 0.2
Depends: R (≥ 4.1.0)
Imports: parallel, ridge, car, glmnet, pls, sva, preprocessCore, GenomicFeatures, genefilter, gdata, tidyverse, readxl, BiocGenerics, GenomicRanges, IRanges, S4Vectors, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene, maftools
Suggests: knitr, rmarkdown
Published: 2021-09-24
Author: Danielle Maeser ORCID iD [aut, cre], Robert Gruener [ctb]
Maintainer: Danielle Maeser <maese005 at umn.edu>
License: GPL-2
NeedsCompilation: no
Materials: README
CRAN checks: oncoPredict results


Reference manual: oncoPredict.pdf
Vignettes: calcPhenotype
Package source: oncoPredict_0.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): oncoPredict_0.1.tgz, r-release (x86_64): not available, r-oldrel: not available
Old sources: oncoPredict archive


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