I asked a question previuosly but I think the answers were not matched with my goal. And I completely confused!
I have a set of data from some microarray dataset that they utilize 2 kind of affymatrix platform for mouse. The data have nearlly the same biological background and only one variable change among them. Moreover, For each study there is the same story, I mean they have different dataset and only one variable have altered. Forexample, in my data for one study, abc add to culture media, then they add abcd. For other microarray data set, they add abc, abcde and abcdef. After using limma package for each microarray dataset separetly, I have extracted a small set of differentially expressed genes that I want. Then I compared them with heirarchical clustring(euclidian for log transformed genes), unexpectedly dataset from one study cluster close toghether and another study fell into other cluster. Before clustring I assume that abc data from two different studies fell into one cluster but my hypothesis was wrong. 1) So would this becase of using different affymatrix and the batch effect? 2) would combat or sva a good package for compansating batch effect? 3) Or a clustring method would be wrong? How can I normilze gene expression data from different microarray studies to be comparable with each other?