Bossers et al. BMC Genomics 2010, 11:112 http://www.biomedcentral.com/1471-2164/11/112 Human brain dataset Fresh-frozen human brain tissue samples were obtained from the Netherlands Brain Bank, Amsterdam (NBB). Written informed consent for a brain autopsy and the use of the material and clinical information for research purposes was obtained by the NBB from the donor or next of kin. Gray matter was isolated from the prefron- tal cortex of 49 individuals (matched for age, sex, post- mortem interval and brain pH) with increasing levels of AD-related neuropathology, as defined by the Braak sta- ging for neurofibrillary tangles [14]. For each of the 7 Braak stages, 7 individuals were included. Tissue dissec- tion was performed using a cryostat. For each sample, between 20 and 30 sections of 50 μm were cut. Grey matter areas were identified by eye and dissected out using pre-chilled scalpels. Tissue yields were typically around 50 mg. Total RNA was isolated using a combi- nation of Trizol-based and RNeasy Mini Kit RNA isola- tion methods. Briefly, samples were homogenized in ice- cold Trizol (Life Technologies, Grand Island, New York, 3 ml Trizol per 100 mg tissue). After phase separation by addition of chloroform, the aqueous phase was mixed with an equal volume of 70% RNAse-free ethanol. Samples were then applied to an RNeasy Mini column (Qiagen, Valencia, California), and processed according to the RNeasy Mini Protocol for RNA Cleanup. Overall, the isolated RNA was of high integrity (average RNA integrity number of of 8.3, range 6.5-9.6, as determined by Agilent 2100 Bioanalyzer analysis). After RNA isolation, for each sample, two 500 ng ali- quots of RNA were linearly amplified and fluorescently labeled with either Cy3-CTP or Cy5-CTP (Perkin Elmer) with the Agilent Low RNA Input Fluorescent Linear Amplification Kit (Agilent Technologies). The most efficient hybridization scheme was calculated with the od function of the SMIDA package (version 0.1) in R. The resulting hybridization setup can be found in Additional files 4 and 6. Equal amounts (1 μg) of Cy3- CTP and Cy5-CTP labeled samples were hybridized to Agilent 44K Whole Human Genome arrays (Part Num- ber G4112A) according to manufacturer’s instructions. Microarray scanning, feature extraction and normaliza- tion procedures were performed as described for the cell line experiment. The full set of normalized expression values is publicly available at http://www.vumc.nl/brain- dataset and as supplementary information to this manu- script (see Additional file 7). Clustering and ANOVA models Clustering of the intensity channels was performed using complete linkage hierarchical clustering. Only probes for which the average log2-transformed intensity (A, as derived from the separate Cy3 or Cy5 channels) was above A = 7 were included. As this procedure Page 11 of 13 removes data from all arrays for a particular probe, the sample sizes are the same for each probe in the final dataset. For the cell-line data, p-values for differential expression between treatments were generated as fol- lows. First, the entire data set was split into two biologi- cally identical parts by simply distinguishing the technical replicates A and B (Additional file 1). The split resulted in cell line data sets C1 and C2. Next, two types of ANOVA models were used per array element. Model 1 represents the ratio-based analysis: Yijk =  +  i +  j +  k( j) +  ijk. (1) Here, μ captures the average gene intensity, τi is the treatment specific effect, hj is the cell line (10 or 19) effect, ak(j) is the array effect, and εijk is the error component. Dye effects have not been incorporated, because the design was balanced for dyes and the data were normalized to remove dye-specific bias. Model 2 lacks the factor ak(j) and hence represents the intensity-based model. The treatment effect is the factor of biological interest, to which an F-test was applied to compute p-values. This resulted in four lists of p-values: ratio-based and intensity-based p-values for technical replicate C1, and ratio-based and intensity- based p-values for technical replicate C2. A similar approach was taken for the human brain data. Each patient was hybridized twice. The resulting set of arrays was split in such a manner that each patient was represented exactly once in both data sets (brain datasets B1 and B2, see Additional file 4). It is noteworthy that the obtained datasets are indeed techni- cal replicates, but not on the level of the experimental design, as is the case for cell line datasets C1 and C2. The cell line effect hj was dropped from the model, and the treatment effect τi now represented the Braak stage. The F-test was performed on the Braak stage factor. Again, two ANOVA models were used: the ratio model which included the array effect ak(j), and the intensity model without array effect. Consequently, four lists of p-values were generated: ratio-based and intensity-based p-values for dataset B1, and ratio-based and intensity- based p-values for dataset B2. We did not apply any multiple testing corrections for our purpose, since a criterion like False Discovery Rate (FDR) might distort the comparison between the models somewhat. Also, since both splits contain an equal num- bers of samples, sample size ‘bias’ is absent. Comparison ratio and intensity data, reproducibility calculations and model selection For the cell line dataset, direct ratio measurements between co-hybridized sample pairs were compared with in silico reconstructed ratios of the two intensity measurements of the same sample pair, as measured on