Physically grounded approach for estimating gene expression from microarray data

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

High-throughput technologies, including gene-expression microarrays, hold great promise for the systems-level study of biological processes. Yet, challenges remain in comparing microarray data from different sources and extracting information about low-abundance transcripts. We demonstrate that these difficulties arise from limitations in the modeling of the data. We propose a physically motivated approach for estimating gene-expression levels from microarray data, an approach neglected in the microarray literature. We separately model the noises specific to sample amplification, hybridization, and fluorescence detection, combining these into a parsimonious description of the variability sources in a microarray experiment. We find that our model produces estimates of gene expression that are reproducible and unbiased. While the details of our model are specific to gene-expression microarrays, we argue that the physically grounded modeling approach we pursue is broadly applicable to other molecular biology technologies.

Original languageEnglish (US)
Pages (from-to)13690-13695
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume107
Issue number31
DOIs
StatePublished - Aug 3 2010

Keywords

  • Process modeling
  • Statistical power

ASJC Scopus subject areas

  • General

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