Nucleic Acids Research, 2012, Vol. 40, Database issue D891 Figure 2. New GWAS tools. Continuing with the IGF-1 example [Yuan1 (28)], we performed a genome-wide association analysis by clicking on the ‘GWAS’ option above the plot shown in Figure 1 (the relevant part of this panel is shown here for convenience). We found signiﬁcant EMMA-corrected peaks for females on chromosomes 2, 10, 13, 14, 15, 17 and 18 (lower panel; green stars were manually overlaid on this plot to ensure visibility of peaks). Interestingly Leduc et al. (29) (the data submitter’s publication for Yuan1) found three of the same in silico QTLs using another method, haplotype association mapping (HAM), which employed the Hidden Markov Model and a set of SNPs at 70K locations (includes imputed calls). We chose to concentrate on the most signiﬁcant peak identiﬁed by these methods on Chr 10 in the vicinity of the Igf1 gene. Using other supporting data sets and bioinformatics tools, Leduc et al. narrowed their results from over 45 genes annotated in the QTL interval to 21 candidate genes. We wondered if we might narrow these results even further by using another new MPD tool for ﬁnding signiﬁcant gene expression correlations (see Figure 3). The new GWAS tool is provided in collaboration with the UCLA Computer Science and Bioinformatics group (ZarLab) (30). MPD is not responsible for the UCLA website or EMMA Server (mouse.cs.ucla.edu/emmaserver). In addition to the highlighted examples (Figures 1–3), MPD has also implemented the following since our last NAR update: . Correlations Center: centralizes, organizes and explains all MPD correlation operations on a single webpage; and provides convenient links to relevant tools (Correlations Center: S14). . Private Analysis Portal: users enter their own experi- mental data and run real-time regression analysis across the entire MPD to identify statistically signiﬁ- cant correlations to existing phenotype and gene ex- pression data (Private Analysis Portal: S15) and . Tool to generate ratio or difference vectors for user-selected MPD measurements: users can view plots and identify independent MPD measurements that are highly correlated to the de novo generated vector (MPD Toolbox Demo: S13; Correlations Center: S14). Additional supplementary data Individual animal data, summary statistics and other metadata are available for downloading in bulk or in customized data sets speciﬁed by the user (Download Center: S16; SNP Downloads: S11). For convenience, we are providing Supplemental Material for general content and information (MPD Content and Quick Facts: S17) and a user’s manual (MPD User Manual and FAQ: S18). HIGH-LEVEL OVERVIEW OF IMPLEMENTATION The speciﬁcs of our implementation have not changed sig- niﬁcantly since our previous update (11). MPD runs on a SUSE Linux/Apache 2 system using open source database, HTML generation and graphics generation software, with custom-written C modules used in performance-critical areas. Phenotype data sets are typic- ally submitted by data contributors as Excel spreadsheets. Genotype and gene expression data sets are usually down- loaded by us from open public resources. Ad hoc process- ing methods are used to integrate these data into our standardized framework. In conjunction with data con- tributors, MPD staff creates supporting documentation in HTML. We add content and perform testing and QA on an internal development node; then this instance is copied over for public release. MPD follows an agile de- velopment philosophy with rapid prototyping and frequent updates; version numbering is not used. For