Resolving Ambiguity in Genome Assembly Using High Performance Computing

DNA sequencing has revolutionised medicine and biology by providing insight into the nature of living organisms. High-throughput shotgun sequencing creates massive numbers of reads in a short period of time and de novo assembly attempts to reconstruct the original sequence, as closely as possible, using these reads. Longer pieces reconstructed by assemblies, shed more light on the underlying organism's biology. Repetitive sequences in the DNA, create ambiguities in the assembly which result in shorter fragments. In this project, we explore the search space of the assembly graph construction using the high performance computing capability of an IBM Blue Gene/Q and develop an algorithm that improves assembly quality through deeper search for valid longer sequences around repeat areas. Our results show that we can increase N50 of contigs by 4% and the number of contigs over 1000bp by up to 7%, however, this extension comes at the cost of using a great deal of computing power.

By: Mahtab Mirmomeni, Tom Conway, Matthias Reumann, Justin Zobel

Published in: RC25439 in 2014


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