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We present MLEHaplo, a maximum likelihood de novo assembly algorithm forreconstructing viral haplotypes in a virus population from paired-end nextgeneration sequencing (NGS) data. Using the pairing information of reads in ourproposed Viral Path Reconstruction Algorithm (ViPRA), we generate a smallsubset of paths from a De Bruijn graph of reads that serve as candidate pathsfor true viral haplotypes. Our proposed method MLEHaplo then generates amaximum likelihood estimate of the viral population using the pathsreconstructed by ViPRA. We evaluate and compare MLEHaplo on simulated datasetsof 1200 base pairs at different sequence coverage, on HCV strains withsequencing errors, and on a lab mixture of five HIV-1 strains. MLEHaploreconstructs full length viral haplotypes having a 100% sequence identity tothe true viral haplotypes in most of the small genome simulated viralpopulations at 250x sequencing coverage. While reference based methods eitherunder-estimate or over-estimate the viral haplotypes, MLEHaplo limits theover-estimation to 3 times the size of true viral haplotypes, reconstructs thefull phylogeny in the HCV to greater than 99% sequencing identity and capturesmore sequencing variation for the HIV-1 strains dataset compared to their knownconsensus sequences.

Maximum Likelihood de novo reconstruction of viral populations using paired end sequencing data