Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data.

Transformation of alignment files improves performance of variant callers for long-read RNA sequencing data.
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DOI:
10.1186/s13059-023-02923-y
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发表时间:
2023-04-24
期刊:
影响因子:
12.3
通讯作者:
--
中科院分区:
生物学1区
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--
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长读段RNA测序(lrRNA-seq)产生关于全长转录本的详细信息,包括新的和样品特异性的同种型。此外,有机会直接从lrRNA-seq数据调用变体。然而,大多数最先进的变异识别子是针对基因组DNA开发的。在这里,有两个目标:首先,我们对GATK,DeepVariant,Clair 3和NanoCaller进行了一个小型基准测试,主要是对PacBio Iso-Seq数据,但也对Nanopore和Illumina RNA-seq数据进行了测试;其次,我们提出了一个处理拼接比对文件的管道,使它们适合基于DNA的调用程序的变体调用。通过这种操作,可以在Iso-seq数据上使用DeepVariant实现高调用性能。在线版本包含补充材料,可在10.1186/s13059-023-02923-y获得。
Long-read RNA sequencing (lrRNA-seq) produces detailed information about full-length transcripts, including novel and sample-specific isoforms. Furthermore, there is an opportunity to call variants directly from lrRNA-seq data. However, most state-of-the-art variant callers have been developed for genomic DNA. Here, there are two objectives: first, we perform a mini-benchmark on GATK, DeepVariant, Clair3, and NanoCaller primarily on PacBio Iso-Seq, data, but also on Nanopore and Illumina RNA-seq data; second, we propose a pipeline to process spliced-alignment files, making them suitable for variant calling with DNA-based callers. With such manipulations, high calling performance can be achieved using DeepVariant on Iso-seq data. The online version contains supplementary material available at 10.1186/s13059-023-02923-y.
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