RT Journal Article
SR Electronic
T1 Interactive Analytics for Very Large Scale Genomic Data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 035295
DO 10.1101/035295
A1 Cuiping Pan
A1 Nicole Deflaux
A1 Gregory McInnes
A1 Michael Snyder
A1 Jonathan Bingham
A1 Somalee Datta
A1 Philip Tsao
YR 2015
UL http://biorxiv.org/content/early/2015/12/24/035295.abstract
AB Large scale genomic sequencing is now widely used to decipher questions in diverse realms such as biological function, human diseases, evolution, ecosystems, and agriculture. With the quantity and diversity these data harbor, a robust and scalable data handling and analysis solution is desired. Here we present interactive analytics using public cloud infrastructure and distributed computing database Dremel and developed according to the standards of Global Alliance for Genomics and Health, to perform information compression, comprehensive quality controls, and biological information retrieval in large volumes of genomic data. We demonstrate that such computing paradigms can provide orders of magnitude faster turnaround for common analyses, transforming long-running batch jobs submitted via a Linux shell into questions that can be asked from a web browser in seconds.