Wang Liguo, Nie Jinfu J, Kocher Jean-Pierre A
Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, Rochester, MN 55905, USA.
Bioinformatics. 2015 May 15;31(10):1668-70. doi: 10.1093/bioinformatics/btv001. Epub 2015 Jan 7.
RNA-seq has been widely used to study the transcriptome. Comparing to microarray, sequencing-based RNA-seq is able to identify splicing variants and single nucleotide variants in one experiment simultaneously. This provides unique opportunity to detect variants that associated with aberrant splicing. Despite the popularity of RNA-seq, no bioinformatics tool has been developed to leverage this advantage to identify variants associated with aberrant splicing.
We have developed PVAAS, a tool to identify single nucleotide variants that associated with aberrant alternative splicing from RNA-seq data. PVAAS works in three steps: (i) identify aberrant splicings; (ii) use user-provided variants or perform variant calling; (iii) assess the significance of association between variants and aberrant splicing events.
RNA测序已被广泛用于研究转录组。与微阵列相比,基于测序的RNA测序能够在一次实验中同时识别剪接变体和单核苷酸变体。这为检测与异常剪接相关的变体提供了独特的机会。尽管RNA测序很受欢迎,但尚未开发出生物信息学工具来利用这一优势识别与异常剪接相关的变体。
我们开发了PVAAS,这是一种从RNA测序数据中识别与异常可变剪接相关的单核苷酸变体的工具。PVAAS分三步工作:(i)识别异常剪接;(ii)使用用户提供的变体或进行变体调用;(iii)评估变体与异常剪接事件之间关联的显著性。