oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data
oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data
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DOI：
10.1093/bib/bbab260
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发表时间：
2021-07-15
影响因子：
9.5
通讯作者：
Huang, Rong Stephanie
中科院分区：
文献类型：
--
作者：
Maeser, Danielle;Gruener, Robert F.;Huang, Rong Stephanie
细胞系药物筛选数据集可用于从药物生物标志物发现到构建药物反应的翻译模型的一系列不同的药物发现应用。之前，我们描述了三种不同的方法，以（1）校正药物敏感性的一般水平，以实现药物特异性生物标志物的发现，（2）预测患者的临床药物反应，以及（3）将这些预测与临床特征相关联，以进行体内药物生物标志物的发现。在这里，我们将这些方法统一并更新到一个R包（oncoPredict）中，以促进这些工具的开发和采用。这种新的OncoPredict R软件包可应用于各种体外和体内环境，用于药物和生物标志物的发现。
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.