4.5 Article

A systematic statistical linear modeling approach to oligonucleotide array experiments

期刊

MATHEMATICAL BIOSCIENCES
卷 176, 期 1, 页码 35-51

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/S0025-5564(01)00107-9

关键词

microarray; mixed model; split plot; probe

资金

  1. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [P01GM045344] Funding Source: NIH RePORTER
  2. NIGMS NIH HHS [GM45344] Funding Source: Medline

向作者/读者索取更多资源

We outline and describe steps for a statistically rigorous approach to analyzing probe-level Affymetrix GeneChip data. The approach employs classical linear mixed models and operates on a gene-by-gene basis. Forgoing any attempts at gene presence or absence calls, the method simultaneously considers the data across all chips in an experiment. Primary output includes precise estimates of fold change (some as low as 1.1), their statistical significance, and measures of array and probe variability. The method can accommodate complex experiments involving many kinds of treatments and can test for their effects at the probe level. Furthermore, mismatch probe data can be incorporated in different ways or ignored altogether. Data from an ionizing radiation experiment on human cell lines illustrate the key concepts. (C) 2002 Published by Elsevier Science Inc.

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