注释
计算生物学
基因亚型
内含子
基因组
纳米孔测序
错误发现率
参考基因组
生物
光学(聚焦)
计算机科学
遗传学
基因
物理
光学
作者
Andrey D. Prjibelski,Alla Mikheenko,Anoushka Joglekar,Alexander Smetanin,Julien Jarroux,Alla Lapidus,Hagen Tilgner
标识
DOI:10.1038/s41587-022-01565-y
摘要
Abstract Annotating newly sequenced genomes and determining alternative isoforms from long-read RNA data are complex and incompletely solved problems. Here we present IsoQuant—a computational tool using intron graphs that accurately reconstructs transcripts both with and without reference genome annotation. For novel transcript discovery, IsoQuant reduces the false-positive rate fivefold and 2.5-fold for Oxford Nanopore reference-based or reference-free mode, respectively. IsoQuant also improves performance for Pacific Biosciences data.
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