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:
文献类型:
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作者:
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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影响因子:
14.9
作者:
NCBI Resource Coordinators
通讯作者:
NCBI Resource Coordinators
影响因子:
46.9
作者:
Poplin, Ryan;Chang, Pi-Chuan;DePristo, Mark A.
通讯作者:
DePristo, Mark A.
影响因子:
30.8
作者:
通讯作者:
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DOI:
10.1038/s41576-020-0236-x
发表时间:
2020-10
期刊:
Nature reviews. Genetics
影响因子:
--
作者:
Logsdon GA;Vollger MR;Eichler EE
通讯作者:
Eichler EE
影响因子:
12.3
作者:
Koboldt DC
通讯作者:
Koboldt DC