Hi Bioconductors, I read vignettes Biobase, esApply and affy because I would like to do a exprSet object with my datas. I load the data geneCov and geneData in the R and exported they to a spread sheet of excell. In excell, I could verify that the data of genes had 501 lines and 27 columns (500 genes and 26 patients), like with the vignete esApply description. These values represent the expression intensities (foreground-background) for each gene? They had not been normalized, yet? On the other hand, when I execute the example given in vignete Biobase, > data(geneCov) > data(geneData) > covN <- list(cov1 = "Covariate 1; 2 levels", cov2 = "Covariate 2; 2 levels", + cov3 = "Covariate 3; 3 levels") > pD <- new("phenoData", pData = geneCov, varLabels = covN) > eSet <- new("exprSet", exprs = geneData, phenoData = pD) and export the eSet data to excell, I see six columns and 13001 lines. I have a data set distributed in six archives: three archives represent one situation (control) and the others three represent another situation (experiment). Each archive are one biological repetition. The software that we use to read the images (.tif) exports the data of foreground, background and the liquid values (foreground-background). If I do an archive where the lines will be the genes and the columns will be the liquid values of the expression for each gene and read it in the R and transforms it in a object exprSet for future analyses I will be making correctly? But, if I want read the fore and the background for each gene in all repettions? How to do the archive in excell? Another question, the covariate archive is important in the analyses or I can create an artificial one? Thanks Marcelo