Kathy, To answer your questions, you may need to know which stages you are trying to integrate your data sets. Roughly speaking, data sets can be integrated at three stages: Say you have two data sets A (affy) and B (cDNA) (1) early stage: first normalize data sets A and B, separately; then somehow rescale normalized A and B; finally put them together (2) middle level stage; first normalize data sets A and B, then calculate effect size (or like meansures/methods) for each gene in A and B, separately; finally you can use random/fixed effects model to integrate the effect sizes (like Choi et al. 2003 method) (3) late stage: first calculate normalize data sets A and B, separately; calculate p-value/test statistic for each gene in each study (standard methods used in single study); finally combine the p-values (say using Fisher method)/test-statistic. There are some bioconductor packages can do (2) and (3) -like RankProd. Pingzhao ======================================== Pingzhao Hu Statistical Analysis Facility The Centre for Applied Genomics (TCAG) The Hospital for Sick Children Research Institute MaRS Centre - East Tower 101 College Street, Room 15-705 Toronto, Ontario, M5G 1L7, Canada Tel.: (416) 813-7654 x6016 Email: phu at sickkids.ca Web: http://www.tcag.ca/statisticalAnalysis.html