BIG DATA for DISCOVERY SCIENCE
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The Big Data for Discovery Science Center (BDDS) - comprised of leading experts in biomedical imaging, genetics, proteomics, and computer science - is taking an "-ome to home" approach toward streamlining big data management, aggregation, manipulation, integration, and the modeling of biological systems across spatial and temporal scales.
 
 

STATISTICAL FUNCTIONAL ANALYSIS




Tools in this category performs statistical analysis to find enriched or overrepresented genes involved in particular pathways or biological processes, and thus provide functional implications of the data. They are conventionally called enrichment analysis. For gene expression (including RNAseq) and proteomics data, they can be analyzed directly from the data management module. For genotype or sequencing data, the results from the association studies are usually the input for these tools.

PANTHER web services have been developed for working with VCF files with SNP data that have been output from BDDS pipelines or other workflows. These services enable users to compare classifications of multiple clusters of lists to a reference list to statistically determine over- or under- representation of pathways and biological processes, including GO ontology classification categories and PANTHER pathways.