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Article

Statistical significance of variables driving systematic variation in high-dimensional data.

Bioinformatics (Oxford, England) - 15 Feb 2015

Chung Neo Christopher, Storey John D

Abstract excerpt

MOTIVATION: There are a number of well-established methods such as principal component analysis (PCA) for automatically capturing systematic variation due to latent variables in large-scale genomic data. PCA and related methods may directly provide a quantitative characterization of a complex biological variable that is otherwise difficult to precisely define or model. An unsolved problem in this context is how...

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PMID: 25336500
DOI: 10.1093/bioinformatics/btu674
PMCID: PMC4325543

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 5 Sept 2026. Manifest publication-graph-cohort-2026-09-05.1.

Source receipt: pubmed, retrieved 5 Sept 2026.

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