title: Microarray standard data set and figures of merit for comparing data processing methods and experiment designs.
abstract: BACKGROUND
  There is a very large and growing level of effort toward improving the platforms, experiment designs, and data analysis methods for microarray expression profiling. Along with a growing richness in the approaches there is a growing confusion among most scientists as to how to make objective comparisons and choices between them for different applications. There is a need for a standard framework for the microarray community to compare and improve analytical and statistical methods.
  
  
  RESULTS
  We report on a microarray data set comprising 204 in-situ synthesized oligonucleotide arrays, each hybridized with two-color cDNA samples derived from 20 different human tissues and cell lines. Design of the approximately 24 000 60mer oligonucleotides that report approximately 2500 known genes on the arrays, and design of the hybridization experiments, were carried out in a way that supports the performance assessment of alternative data processing approaches and of alternative experiment and array designs. We also propose standard figures of merit for success in detecting individual differential expression changes or expression levels, and for detecting similarities and differences in expression patterns across genes and experiments. We expect this data set and the proposed figures of merit will provide a standard framework for much of the microarray community to compare and improve many analytical and statistical methods relevant to microarray data analysis, including image processing, normalization, error modeling, combining of multiple reporters per gene, use of replicate experiments, and sample referencing schemes in measurements based on expression change.
  Expression data and supplementary information are available at http://www.rii.com/publications/2003/HE_SDS.htm
authors.affiliation: Rosetta Inpharmatics Inc., 12 040 115th Avenue Northeast, Kirkland, WA 98034, USA. yudong_he@merck.com
authors.forename: Yudong D
authors.initials: YD
authors.lastname: He
authors.forename: Hongyue
authors.initials: H
authors.lastname: Dai
authors.forename: Eric E
authors.initials: EE
authors.lastname: Schadt
authors.forename: Guy
authors.initials: G
authors.lastname: Cavet
authors.forename: Stephen W
authors.initials: SW
authors.lastname: Edwards
authors.forename: Sergey B
authors.initials: SB
authors.lastname: Stepaniants
authors.forename: Sven
authors.initials: S
authors.lastname: Duenwald
authors.forename: Robert
authors.initials: R
authors.lastname: Kleinhanz
authors.forename: Allan R
authors.initials: AR
authors.lastname: Jones
authors.forename: Daniel D
authors.initials: DD
authors.lastname: Shoemaker
authors.forename: Roland B
authors.initials: RB
authors.lastname: Stoughton
mesh_terms: D001483:Base Sequence; D018076:DNA, Complementary / Q000235:genetics; D030561:Databases, Nucleic Acid / Q000592:standards*; D019544:Equipment Failure Analysis / Q000379:methods / Q000592:standards; D020869:Gene Expression Profiling / Q000379:methods / Q000592:standards*; D005786:Gene Expression Regulation / Q000235:genetics; D006801:Humans; D008969:Molecular Sequence Data; D020411:Oligonucleotide Array Sequence Analysis / Q000295:instrumentation / Q000379:methods* / Q000592:standards*; D011786:Quality Control; D012015:Reference Standards; D016415:Sequence Alignment / Q000379:methods / Q000592:standards; D017422:Sequence Analysis, DNA / Q000379:methods / Q000592:standards*
chemical_list: D018076:DNA, Complementary