|Martin Leach, chief information officer at the Broad Institute|
There are plenty of analysis tools in genomics that highlight variants in the DNA code, aiding in the discovery of genetic biomarkers for disease risk. And this is a solid example of Big Data analytics. Yet researchers at the Broad Institute and other leading genomics labs have developed informatics tools and other systems to integrate multiple types of data--including genomic, phenotypic, proteomic and clinical data. And the ability to correlate diverse and large datasets could provide a clearer understanding of diseases.
To accomplish this feat of analyzing mixed batches of Big Data, Jill Mesirov, chief informatics officer at the Broad, has worked with colleagues to develop open source software called the Integrative Genomics Viewer. Beyond providing sequence alignment like scores of other informatics tools, IGV enables researchers to view omics and array data alongside clinical findings. Also, GNS Healthcare has pioneered a machine-learning technology that factors in diverse datasets to create predictive models and biomarker signatures that can be used to, for instance, help drug developers to identify patients for clinical trials.