Sstack: An R package for stacking with applications to scenarios involving sequential addition of samples and features

Kevin Matlock, Raziur Rahman, Souparno Ghosh, Ranadip Pal

Research output: Contribution to journalArticle

Abstract

Biological processes are characterized by a variety of different genomic feature sets. However, often times when building models, portions of these features are missing for a subset of the dataset. We provide a modeling framework to effectively integrate this type of heterogeneous data to improve prediction accuracy. To test our methodology, we have stacked data from the Cancer Cell Line Encyclopedia to increase the accuracy of drug sensitivity prediction. The package addresses the dynamic regime of information integration involving sequential addition of features and samples.

Original languageEnglish
Pages (from-to)3143-3145
Number of pages3
JournalBioinformatics
Volume35
Issue number17
DOIs
StatePublished - Sep 1 2019

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