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

Bioinformatics, ISSN: 1460-2059, Vol: 35, Issue: 17, Page: 3143-3145
2019
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Article Description

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.

Bibliographic Details

Kevin Matlock; Raziur Rahman; Souparno Ghosh; Ranadip Pal; John Hancock

Oxford University Press (OUP)

Mathematics; Biochemistry, Genetics and Molecular Biology; Computer Science

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