Your browser doesn't support javascript.
Analysis of error profiles in deep next-generation sequencing data.
Genome Biol ; 20(1): 50, 2019 03 14.
Artigo em Inglês | MEDLINE | ID: mdl-30867008


Sequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.


By evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target-enrichment PCR led to ~ 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1 ~ 0.01% frequency with the current NGS technology by applying in silico error suppression.


We present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.





Texto completo: Disponível Coleções: Bases de dados internacionais Base de dados: MEDLINE Assunto principal: Software / Reação em Cadeia da Polimerase / Análise de Sequência de DNA / Sequenciamento de Nucleotídeos em Larga Escala / Neoplasias Tipo de estudo: Estudo de casos e controles Limite: Humanos Idioma: Inglês Revista: Genome Biol Assunto da revista: Biologia Molecular / Genética Ano de publicação: 2019 Tipo de documento: Artigo País de afiliação: Estados Unidos