PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations.

SUMMARY: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies in humans. This online tool facilitates 'phenome scans', where genetic variants are cross-referenced for association with many phenotypes of different types. Here we present a major update of PhenoScanner ('PhenoScanner V2'), including over 150 million genetic variants and more than 65 billion associations (compared to 350 million associations in PhenoScanner V1) with diseases and traits, gene expression, metabolite and protein levels, and epigenetic markers. The query options have been extended to include searches by genes, genomic regions and phenotypes, as well as for genetic variants. All variants are positionally annotated using the Variant Effect Predictor and the phenotypes are mapped to Experimental Factor Ontology terms. Linkage disequilibrium statistics from the 1000 Genomes project can be used to search for phenotype associations with proxy variants. AVAILABILITY AND IMPLEMENTATION: PhenoScanner V2 is available at www.phenoscanner.medschl.cam.ac.uk.

MitoMiner: a data warehouse for mitochondrial proteomics data.

MitoMiner (http://mitominer.mrc-mbu.cam.ac.uk/) is a data warehouse for the storage and analysis of mitochondrial proteomics data gathered from publications of mass spectrometry and green fluorescent protein tagging studies. In MitoMiner, these data are integrated with data from UniProt, Gene Ontology, Online Mendelian Inheritance in Man, HomoloGene, Kyoto Encyclopaedia of Genes and Genomes and PubMed. The latest release of MitoMiner stores proteomics data sets from 46 studies covering 11 different species from eumetazoa, viridiplantae, fungi and protista. MitoMiner is implemented by using the open source InterMine data warehouse system, which provides a user interface allowing users to upload data for analysis, personal accounts to store queries and results and enables queries of any data in the data model. MitoMiner also provides lists of proteins for use in analyses, including the new MitoMiner mitochondrial proteome reference sets that specify proteins with substantial experimental evidence for mitochondrial localization. As further mitochondrial proteomics data sets from normal and diseased tissue are published, MitoMiner can be used to characterize the variability of the mitochondrial proteome between tissues and investigate how changes in the proteome may contribute to mitochondrial dysfunction and mitochondrial-associated diseases such as cancer, neurodegenerative diseases, obesity, diabetes, heart failure and the ageing process.