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PMID: 11867082 Published · ppublish English Journal Article Research Support, U.S. Gov't, P.H.S.

A systematic statistical linear modeling approach to oligonucleotide array experiments.

Mathematical biosciences ·Vol. 176 ·No. 1 ·2002-03-00 ·Pages 35-51

Chu TM, Weir B, Wolfinger R

Abstract

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.

MeSH Terms
Cells, Cultured Humans Models, Statistical Oligonucleotide Array Sequence Analysis/methods Radiation, Ionizing Transcription, Genetic
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Chu Tzu Ming
Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA.
Weir Bruce
Wolfinger Russ
Article Info
Journal
Mathematical biosciences
Abbr.
Math Biosci
ISSN
0025-5564
Published
2002-03-00
Pages
35-51
Language
English
Region
United States
NLM ID
0103146
Subset
IM
Grants
NIGMS NIH HHS · GM45344 · United States
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