Evaluating long-read RNA-sequencing analysis tools with in silico mixtures

被引：1
|
作者：
Dong, Xueyi [1 ]
Ritchie, Matthew E. [1 ]
机构：
[1] Walter & Eliza Hall Inst Med Res, Parkville, Vic, Australia
来源：
NATURE METHODS | 2023年 / 20卷 / 11期
关键词：
D O I：
10.1038/s41592-023-02027-2
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
We conducted a comprehensive long-read RNA sequencing (RNA-seq) benchmarking experiment by combining spike-ins and in silico mixtures to establish a ground-truth dataset. We used long- and short-read RNA-seq technology to deeply sequence samples and compared the performance of a range of analysis tools on these data.
引用
收藏
页码：1643 / 1644
页数：2
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