For each of the individual studies, a series of analyses were performed. Each array (representing a single patient) was subjected to a quality control (QC) analysis for chip-level parameters (e.g. scaling factor, gene calls, control gene ratios, average correlation) with respect to the reference distribution for those parameters across the arrays. This QC analysis is represented with both graphical representations (e.g. heatmaps, scatter plots, and histograms (Figure ​(Figure1))1)) and table summaries, allowing users to readily identify those arrays determined to be outliers in the study. A total of 41 clinical demographic variables (Tables ​(Tables1,1, ​,2,2, ​,3,3, ​,4)4) were assessed for their effects on a gene-by-gene basis. Continuous variables and ordered categorical variables were cut at values as close as possible to the median (e.g. PMI>30 vs. PMI<30; Drug Use = 'Heavy' vs. Drug Use = 'None, Light, Moderate'). The genes determined to be most significant (p-value<0.01 and fold change >1.3) for each demographic variable is reported in a table, accompanied by a summary of the percentage of significant genes for each variable (Figure ​(Figure2).2). Each gene found to be significant for a demographic variable links to a gene-centric page (discussed in Gene details page section). Such results allow researchers to determine markers that are related to lifestyle or clinical demographical information and identify confounding variables within a disease class.

Within this pathway/GO detail page is a comprehensive summary of the gene expression profiles for each gene that is mapped to the associated pathway or GO term within each separate disease class. A confidence interval boxplot is provided within each disease comparison inclusive of every gene mapped to that pathway or GO term queried in the study (Figure ​(Figure7),7), along with a link to the pathway network representation provided by KEGG. Such results allow researchers to understand the most regulated biological mechanisms and cellular sites for each disease class.

For every probe across the 6 array platforms, primary annotations were determined such that each probe is mapped to either a gene name or EST identifier (refer to Bioinformatics mappings section for mapping criteria). So each gene summary page contains probe-level information for all of the 6 array platforms and 12 studies within the database. In addition to general bioinformatics annotations (e.g. biological summary, LocusLink ID, PubMed search link, and gene symbol) and pathway/GO mappings (associations with gene that link to pathway/GO-centric pages), this page contains gene expression summaries for every probe that maps to this gene across all studies (Figure ​(Figure8).8). A cross study 'consensus' fold change was calculated for each gene and disease/demographic comparison, based on a weighted combination of the individual fold changes and standard errors for the probes that map to each gene across the platforms/studies. Weights were determined in a probeset-specific manner to account for the differing levels of precision associated with each probeset that maps to a given gene across the platforms. Confidence interval boxplots inclusive of each probe for the gene on this page are provided for the following: normalized expression across all patients, fold changes within each disease class, percent present calls for the former two comparisons, and all 41 demographic variables for the gene (Figure ​(Figure9).9). Additionally, there is a general search engine that supports queries of gene name, symbol, pathway, GO term, and LocusLink ID designed for direct access to any gene detail page or pathway/GO detail page.