MUSIC

High-throughput DNA sequencers are becoming indispensable in our understanding of diseases atmolecular level, in marker-assisted selection in agricultureand in microbial genetics research. These sequencinginstruments produce enormous amount of data (oftenterabytes of raw data in a month) that requires efficientanalysis, management and interpretation. The commonlyused sequencing instrument today produces billions ofshort reads (upto 150 bases) from each run. The first stepin the data analysis step is alignment of these short reads tothe reference genome of choice. There are different opensource algorithms available for sequence alignment to thereference genome. These tools normally have a highcomputational overhead, both in terms of number ofprocessors and memory. Here, we propose a hybrid computing environment called MUSIC (Mapping USInghybrid Computing) for one of the most popular open sourcesequence alignment algorithm, BWA, using acceleratorsthat show significant improvement in speed over the serialcode