Work

Partial least squares: a versatile tool for the analysis of high-dimensional genomic data

Year: 2006

Type: article

Abstract: 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.

Source: Briefings in Bioinformatics

DOI: 10.1093/bib/bbl016

Authors: A.-L. Boulesteix, K. Strimmer

Institutions: Technical University of Munich, Ludwig-Maximilians-Universität München

Language: English

Topic: Gene expression and cancer classification

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

OpenAlex ID: W2097057782

FWCI: 6.962

Cites: 75

Cited by: 836

Related to: 10