使用配对末端测序数据的病毒群体的最大可能性从头重建
Maximum Likelihood de novo reconstruction of viral populations using paired end sequencing data
摘要：
我们提出了MLEHaplo，一种最大似然从头组装算法，用于从配对末端下一代测序（NGS）数据重建病毒群体中的病毒单倍型。在我们提出的病毒路径重建算法（ViPRA）中使用读段的配对信息，我们从读段的De Bruijn图中生成一小部分路径，作为真正病毒单倍型的候选路径。然后，我们提出的方法MLEHaplo使用ViPRA重建的路径生成病毒群体的最大似然估计。我们评估和比较MLEHaplo在不同序列覆盖率的1200个碱基对的模拟数据集上，在具有测序错误的HCV毒株上，以及在五种HIV-1毒株的实验室混合物上。MLEHaplo在250 x测序覆盖率下重建全长病毒单倍型，与大多数小基因组模拟病毒群体中的真实病毒单倍型具有100%序列同一性。虽然基于参考的方法低估或高估了病毒单倍型，但MLEHaplo将高估限制在真实病毒单倍型大小的3倍，将HCV中的完整同源性重建为大于99%的测序同一性，并与其已知的共有序列相比，捕获HIV-1毒株数据集的更多测序变异。
英文摘要：
We present MLEHaplo, a maximum likelihood de novo assembly algorithm for reconstructing viral haplotypes in a virus population from paired-end next generation sequencing (NGS) data. Using the pairing information of reads in our proposed Viral Path Reconstruction Algorithm (ViPRA), we generate a small subset of paths from a De Bruijn graph of reads that serve as candidate paths for true viral haplotypes. Our proposed method MLEHaplo then generates a maximum likelihood estimate of the viral population using the paths reconstructed by ViPRA. We evaluate and compare MLEHaplo on simulated datasets of 1200 base pairs at different sequence coverage, on HCV strains with sequencing errors, and on a lab mixture of five HIV-1 strains. MLEHaplo reconstructs full length viral haplotypes having a 100% sequence identity to the true viral haplotypes in most of the small genome simulated viral populations at 250x sequencing coverage. While reference based methods either under-estimate or over-estimate the viral haplotypes, MLEHaplo limits the over-estimation to 3 times the size of true viral haplotypes, reconstructs the full phylogeny in the HCV to greater than 99% sequencing identity and captures more sequencing variation for the HIV-1 strains dataset compared to their known consensus sequences.
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