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PMID: 11860205 Published · ppublish English Journal Article Review

Microarray data quality analysis: lessons from the AFGC project. Arabidopsis Functional Genomics Consortium.

Plant molecular biology ·Vol. 48 ·No. 1-2 ·2002-01-00 ·Pages 119-31

Finkelstein D, Ewing R, Gollub J, Sterky F, Cherry JM, Somerville S

Abstract

Genome-wide expression profiling with DNA microarrays has and will provide a great deal of data to the plant scientific community. However, reliability concerns have required the development data quality tests for common systematic biases. Fortunately, most large-scale systematic biases are detectable and some are correctable by normalization. Technical replication experiments and statistical surveys indicate that these biases vary widely in severity and appearance. As a result, no single normalization or correction method currently available is able to address all the issues. However, careful sequence selection, array design, experimental design and experimental annotation can substantially improve the quality and biological of microarray data. In this review, we discuss these issues with reference to examples from the Arabidopsis Functional Genomics Consortium (AFGC) microarray project.

MeSH Terms
Arabidopsis/genetics Genes, Plant/genetics Genetic Variation Genome, Plant Genomics Oligonucleotide Array Sequence Analysis/methods,standards Reproducibility of Results
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Finkelstein David
Carnegie Institution of Washington, Department of Plant Biology, Stanford, CA 94305, USA. [email protected]
Ewing Rob
Gollub Jeremy
Sterky Fredrik
Cherry J Michael
Somerville Shauna
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Article Info
Journal
Plant molecular biology
Abbr.
Plant Mol Biol
ISSN
0167-4412
Published
2002-01-00
Pages
119-31
Language
English
Region
Netherlands
NLM ID
9106343
Subset
IM
Analysis Services
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