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

Danielle Maeser, Robert F. Gruener, Rong Stephanie Huang

Research output: Contribution to journalArticlepeer-review

569 Scopus citations

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.

Original languageEnglish (US)
Article numberbbab260
JournalBriefings in Bioinformatics
Volume22
Issue number6
DOIs
StatePublished - Nov 1 2021

Bibliographical note

Publisher Copyright:
© 2021 The Author(s). Published by Oxford University Press. All rights reserved. For Permissions, please email: [email protected].

Keywords

  • biomarker identification
  • drug discovery
  • drug response prediction

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