Sufficient principal component regression for pattern discovery in transcriptomic data
Lei Ding,
Gabriel E. Zentner,
Daniel J. McDonald
Abstract:Methods for global measurement of transcript abundance such as microarrays and RNAseq generate datasets in which the number of measured features far exceeds the number of observations. Extracting biologically meaningful and experimentally tractable insights from such data therefore requires high-dimensional prediction. Existing sparse linear approaches to this challenge have been stunningly successful, but some important issues remain. These methods can fail to select the correct features, predict poorly relat… Show more
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