期刊
BRIEFINGS IN BIOINFORMATICS
卷 8, 期 1, 页码 32-44出版社
OXFORD UNIV PRESS
DOI: 10.1093/bib/bb1016
关键词
partial least squares (PLS); high-dimensional genomic data; gene expression; classification; dimension reduction
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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