oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data

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ID: 295653
2021
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Ranked #20 of 55 articles by views in Briefings in bioinformatics

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Abstract
Cell line drug screening datasets can be utilized for a range of different drug discovery applications from drug biomarker discovery to building translational models of drug response. Previously, we described three separate methodologies to (1) correct for general levels of drug sensitivity to enable drug-specific biomarker discovery, (2) predict clinical drug response in patients and (3) associate these predictions with clinical features to perform in vivo drug biomarker discovery. Here, we unite and update these methodologies into one R package (oncoPredict) to facilitate the development and adoption of these tools. This new OncoPredict R package can be applied to various in vitro and in vivo contexts for drug and biomarker discovery.
Reference Key
openalex_W3182293965 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Danielle Maeser, Robert F. Gruener, R. Stephanie Huang
Journal Briefings in bioinformatics
Year 2021
DOI
10.1093/bib/bbab260
URL
https://doi.org/10.1093/bib/bbab260
Keywords Keywords not found

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