Center for Algorithmic Biotechnology, Institute of Translational Biomedicine, St. Petersburg State University, St. Petersburg, Russia.
Department of Computer Science, University of Helsinki, Helsinki, Finland.
Nat Biotechnol. 2023 Jul;41(7):915-918. doi: 10.1038/s41587-022-01565-y. Epub 2023 Jan 2.
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.
为新测序的基因组做注释并从长读长 RNA 数据中确定选择性异构体是复杂且尚未完全解决的问题。在这里,我们提出了 IsoQuant,这是一种使用内含子图的计算工具,它可以准确地重建有参考基因组注释和无参考基因组注释的转录本。对于新的转录本发现,IsoQuant 分别将 Oxford Nanopore 基于参考或无参考模式的假阳性率降低了五倍和 2.5 倍。IsoQuant 还提高了 Pacific Biosciences 数据的性能。