Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis.
Error correction enables use of Oxford Nanopore technology for reference-free transcriptome analysis.
复制标题
错误校正使得能够使用Oxford Nanopore技术进行无参考转录组分析。
DOI：
10.1038/s41467-020-20340-8
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发表时间：
2021-01-04
影响因子：
16.6
通讯作者：
Medvedev P
中科院分区：
文献类型：
--
作者：
Sahlin K;Medvedev P
牛津纳米孔(ONT)是一项领先的长阅读技术，它通过从端到端对大多数转录本进行排序的能力，使转录组分析发生了革命性的变化。这极大地提高了我们研究转录起始、终止和选择性剪接等转录机制多样性的能力。然而，ONT仍然受到高错误率的困扰，到目前为止，它的范围仅限于基于参考的分析。当参考文献不可用或由于参考文献偏倚而不是可行的选择时，纠错是重建已测序转录产物和转录产物下游序列分析的关键步骤。在这篇文章中，我们提出了一种新的计算方法来修正ONT的cDNA测序数据，称为isON校正。在纠错过程中，IsONright能够联合使用基因的所有异构体，从而使其能够在低测序深度下纠正读数。我们能够获得98.9%-99.6%的中位准确率，证明了将经济有效的cDNA全转录长度测序用于无参考转录组分析的可行性。应用于转录组分析的纳米孔测序技术存在着高错误率的问题，这在很大程度上限制了它们在很大程度上局限于基于参考的分析。在这里，作者提出了一种用于转录组分析的计算误差校正方法，将中位错误率从~7%降低到~1%。
Oxford Nanopore (ONT) is a leading long-read technology which has been revolutionizing transcriptome analysis through its capacity to sequence the majority of transcripts from end-to-end. This has greatly increased our ability to study the diversity of transcription mechanisms such as transcription initiation, termination, and alternative splicing. However, ONT still suffers from high error rates which have thus far limited its scope to reference-based analyses. When a reference is not available or is not a viable option due to reference-bias, error correction is a crucial step towards the reconstruction of the sequenced transcripts and downstream sequence analysis of transcripts. In this paper, we present a novel computational method to error correct ONT cDNA sequencing data, called isONcorrect. IsONcorrect is able to jointly use all isoforms from a gene during error correction, thereby allowing it to correct reads at low sequencing depths. We are able to obtain a median accuracy of 98.9–99.6%, demonstrating the feasibility of applying cost-effective cDNA full transcript length sequencing for reference-free transcriptome analysis. Nanopore sequencing technologies applied to transcriptome analysis suffer from high error rates, limiting them largely to reference-based analyses. Here, the authors develop a computational error correction method for transcriptome analysis that reduces the median error rate from ~7% to ~1%.
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影响因子：
11
作者：
Clark, Michael B.;Wrzesinski, Tomasz;Tunbridge, Elizabeth M.
通讯作者：
Tunbridge, Elizabeth M.
影响因子：
1.7
作者：
Sahlin, Kristoffer;Medvedev, Paul
通讯作者：
Medvedev, Paul
影响因子：
7
作者：
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通讯作者：
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影响因子：
16.6
作者：
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通讯作者：
Vollmers C
影响因子：
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作者：
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