RNA sequencing (RNA-seq) is a powerful technology for studying human transcriptome variation. We introduce PAIRADISE (Paired Replicate Analysis of Allelic Differential Splicing Events), a method for detecting allele-specific alternative splicing (ASAS) from RNA-seq data. Unlike conventional approaches that detect ASAS events one sample at a time, PAIRADISE aggregates ASAS signals across multiple individuals in a population. By treating the two alleles of an individual as paired, and multiple individuals sharing a heterozygous SNP as replicates, we formulate ASAS detection using PAIRADISE as a statistical problem for identifying differential alternative splicing from RNA-seq data with paired replicates. PAIRADISE outperforms alternative statistical models in simulation studies. Applying PAIRADISE to replicate RNA-seq data of a single individual and to population-scale RNA-seq data across many individuals, we detect ASAS events associated with genome-wide association study (GWAS) signals of complex traits or diseases. Additionally, PAIRADISE ASAS analysis detects the effects of rare variants on alternative splicing. PAIRADISE provides a useful computational tool for elucidating the genetic variation and phenotypic association of alternative splicing in populations.

RNA测序（RNA-seq）是研究人类转录组变异的强大技术。我们介绍了PAIRADISE（等位基因差异剪接事件的配对复制分析），一种从RNA序列数据中检测等位基因特异性剪接（ASAS）的方法。与一次检测一个样本的ASAS事件的传统方法不同，PAIRADISE会在人群中的多个个体之间聚合ASAS信号。通过将一个个体的两个等位基因配对，并将共享一个杂合SNP的多个个体作为重复，我们使用PAIRADISE制定了ASAS检测，作​​为用于从具有配对重复的RNA-seq数据中识别差异性可变剪接的统计问题。在模拟研究中，PAIRADISE优于其他统计模型。应用PAIRADISE复制单个个体的RNA-seq数据并应用于许多个体的人口规模的RNA-seq数据，我们检测到与复杂性状或疾病的全基因组关联研究（GWAS）信号相关的ASAS事件。此外，PAIRADISE ASAS分析可检测稀有变体对替代剪接的影响。PAIRADISE提供了一个有用的计算工具，用于阐明群体中可变剪接的遗传变异和表型关联。