RT Journal Article
SR Electronic
T1 Viral Quasispecies Reconstruction via Correlation Clustering
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 096768
DO 10.1101/096768
A1 Somsubhra Barik
A1 Shreepriya Das
A1 Haris Vikalo
YR 2016
UL http://biorxiv.org/content/early/2016/12/26/096768.abstract
AB RNA viruses are characterized by high mutation rates that give rise to populations of closely related viral genomes, the so-called viral quasispecies. The underlying genetic heterogeneity occurring as a result of natural mutation-selection process enables the virus to adapt and proliferate in face of changing conditions over the course of an infection. Determining genetic diversity (i.e., inferring viral haplotypes and their proportions in the population) of an RNA virus is essential for the understanding of its origin and mutation patterns, and the development of effective drug treatments. In this paper we present QSdpR, a novel correlation clustering formulation of the quasispecies reconstruction problem which relies on semidefinite programming to accurately estimate the sub-species and their frequencies in a mixed population. Extensive comparisons with existing methods are presented on both synthetic and real data, demonstrating efficacy and superior performance of QSdpR.