Using ANOVA for gene selection from microarray studies of the nervous system.
Methods are presented for detecting differential expression using statistical hypothesis testing methods including analysis of variance (ANOVA). Practicalities of experimental design, power, and sample size are discussed. Methods for multiple testing correction and their application are described. Instructions for running typical analyses are given in the R programming environment. R code and the sample data set used to generate the examples are available at http://microarray.cpmc.columbia.edu/pavlidis/pub/aovmethods/.
Department of Biomedical Informatics and Columbia Genome Center, Columbia University, Rm 121J, 1150 St. Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu
Paul
P
Pavlidis
D000704:Analysis of Variance; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data; D009420:Nervous System / Q000737:chemistry*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods* / Q000706:statistics & numerical data*; D013698:Templates, Genetic