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Error correction of next-generation sequencing data and reliable estimation of HIV quasispecies

机译:下一代测序数据的错误校正和HIV准种的可靠估计

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Next-generation sequencing technologies can be used to analyse genetically heterogeneous samples at unprecedented detail. The high coverage achievable with these methods enables the detection of many low-frequency variants. However, sequencing errors complicate the analysis of mixed populations and result in inflated estimates of genetic diversity. We developed a probabilistic Bayesian approach to minimize the effect of errors on the detection of minority variants. We applied it to pyrosequencing data obtained from a 1.5-kb-fragment of the HIV-1 gag/pol gene in two control and two clinical samples. The effect of PCR amplification was analysed. Error correction resulted in a two- and five-fold decrease of the pyrosequencing base substitution rate, from 0.05% to 0.03% and from 0.25% to 0.05% in the non-PCR and PCR-amplified samples, respectively. We were able to detect viral clones as rare as 0.1% with perfect sequence reconstruction. Probabilistic haplotype inference outperforms the counting-based calling method in both precision and recall. Genetic diversity observed within and between two clinical samples resulted in various patterns of phenotypic drug resistance and suggests a close epidemiological link. We conclude that pyrosequencing can be used to investigate genetically diverse samples with high accuracy if technical errors are properly treated.
机译:下一代测序技术可用于以前所未有的细节分析遗传异质样品。这些方法可实现的高覆盖范围使得能够检测许多低频变量。但是,测序错误使混合种群的分析复杂化,并导致对遗传多样性的估计过高。我们开发了一种概率贝叶斯方法,以最大程度地减少错误对少数派变体检测的影响。我们将其应用于从两个对照和两个临床样本中的HIV-1 gag / pol基因的1.5 kb片段获得的焦磷酸测序数据中。分析了PCR扩增的效果。错误校正导致焦磷酸测序碱基取代率分别下降了两倍和五倍,分别在非PCR和PCR扩增样品中分别从0.05%降低至0.03%和从0.25%降低至0.05%。通过完美的序列重建,我们能够检测到0.1%的罕见病毒克隆。概率单倍型推理在准确性和查全率方面均优于基于计数的调用方法。在两个临床样品之间和之间观察到的遗传多样性导致了表型耐药的各种模式,并表明了流行病学的紧密联系。我们得出的结论是,如果技术错误得到正确处理,焦磷酸测序可用于高精度调查遗传多样的样品。

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