Over the last decade, the cost of producing genomic sequences has dropped dramatically due to the current so-called next-generation sequencing methods. However, these next-generation sequencing methods are critically dependent on fast and sophisticated data processing methods for aligning a set of query sequences to a reference genome using rich string matching models. The focus of this work is on the design, development and evaluation of a data processing system for this crucial \u201cshort read alignment\u201d problem. Our system, called WHAM, employs hash-based indexing methods and bitwise operations for sequence alignments. It allows rich match models and it is significantly faster than the existing state-of-the-art methods. In addition, its relative speedup over the existing method is poised to increase in the future in which read sequence lengths will increase.<\/p>\n","protected":false},"excerpt":{"rendered":"
Over the last decade, the cost of producing genomic sequences has dropped dramatically due to the current so-called next-generation sequencing methods. However, these next-generation sequencing methods are critically dependent on fast and sophisticated data processing methods for aligning a set of query sequences to a reference genome using rich string matching models. 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