oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 34260682.
- Also identified by DOI 10.1093/bib/bbab260 and PMC identifier 8574972.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
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.
Medical subject headings
- Antineoplastic Agents
- Biomarkers, Tumor
- Software