Journal
BRIEFINGS IN BIOINFORMATICS
Volume 8, Issue 1, Pages 32-44Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bib/bb1016
Keywords
partial least squares (PLS); high-dimensional genomic data; gene expression; classification; dimension reduction
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Partial least squares (PLS) is an efficient statistical regression technique that is highly suited for the analysis of genomic and proteomic data. In this article, we review both the theory underlying PLS as well as a host of bioinformatics applications of PLS. In particular, we provide a systematic comparison of the PLS approaches currently employed, and discuss analysis problems as diverse as, e.g. tumor classification from transcriptome data, identification of relevant genes, survival analysis and modeling of gene networks and transcription factor activities.
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