Hi all, Please help me with any of the problems below, really appreciate your kind help! 1) I have 16 tumor samples and each one has a corresponding normal sample(16+16). For one pair, there is a metastasis sample. When I analyzed the data using limma package, is it right that I fit linear model, and compare two contrasts of Tumor vs. Normal, and Metastasis vs. Normal? Or should I ignore that 1 metastasis sample and just use paired ttest to compare Tumor vs. Normal? 2) The neqc() function has background corrected and normalized our data (tumor, normal, and metastasis samples) based on control probes. So when I generated a heatmap, is it right that I included both the Tumor and Normal samples in columns? Or I should only show tumor samples, but the values are tumor over normal (or tumor normalized with normal)? What does the value of each grid indicate? 3) I have four chips of microarray experiments, and therefore four data sets. I combined them together and read in them as one file use read.ilmn(), and I combined all the control probe files into one and read it in. I just followed the limma user guide and use neqc() for background correction and normalization. Is it good enough? Do I need to consider within array and between array normalization? Thank you for your time! Best, Xiayu [[alternative HTML version deleted]]