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
In views: Omics
CRAN checks: oncoPredict results


Reference manual: oncoPredict.pdf
Vignettes: calcPhenotype


Package source: oncoPredict_0.2.tar.gz
Windows binaries: r-devel: oncoPredict_0.2.zip, r-release: oncoPredict_0.2.zip, r-oldrel: oncoPredict_0.2.zip
macOS binaries: r-release (arm64): oncoPredict_0.2.tgz, r-oldrel (arm64): oncoPredict_0.2.tgz, r-release (x86_64): oncoPredict_0.2.tgz
Old sources: oncoPredict archive


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