Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness. Issue 18 (December 2015)

• Record Type: Journal Article
• Authors: Jayasundara, Duleepa; Saeed, I; Chang, BC; Tang, Sen-Lin; Halgamuge, Saman
• Is Part Of: BMC bioinformatics. Volume 16:Issue 18(2015)
• Page Start: 1
• Page End: 12
• Publication Date: 2015-12
• Subjects: viral quasispecies -- quasispecies spectrum reconstruction -- strain richness -- probabilistic estimation; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/1471-2105-16-S18-S3
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract Background Estimating the number of different species (richness ) in a mixed microbial population has been a main focus in metagenomic research. Existing methods of speciesrichness estimation ride on the assumption that the reads in each assembled contig correspond to only one of the microbial genomes in the population. This assumption and the underlying probabilistic formulations of existing methods are not useful for quasispecies populations where the strains are highly genetically related. The lack of knowledge on the number of different strains in a quasispecies population is observed to hinder theprecision of existing Viral Quasispecies Spectrum Reconstruction (QSR) methods due to the uncontrolled reconstruction of a large number ofin silico false positives. In this work, we formulated a novel probabilistic method for strain richness estimation specifically targeting viral quasispecies. By using this approach we improved our recently proposed spectrum reconstruction pipeline ViQuaS to achieve higher levels of precision in reconstructed quasispecies spectra without compromising the recall rates. We also discuss how one other existing popular QSR method named ShoRAH can be improved using this new approach. Results On benchmark data sets, our estimation method provided accurate richness estimates (< 0.2 median estimation error) and improved the precision of ViQuaS by 2%-13% and F-score by 1%-9% without compromising the recall rates. We also demonstrate that our estimation method can be used to improve the precision and F-score of ShoRAH by 0%-7% and 0%-5% respectively. Conclusions The proposed probabilistic estimation method can be used to estimate the richness of viral populations with a quasispecies behavior and to improve the accuracy of the quasispecies spectra reconstructed by the existing methods ViQuaS and ShoRAH in the presence of a moderate level of technical sequencing errors. Availability http://sourceforge.net/projects/viquas/