The excision of introns from pre-mRNA is an essential step in mRNA processing. We developed LeafCutter to study sample and population variation in intron splicing. LeafCutter identifies variable splicing events from short-read RNA-seq data and finds events of high complexity. Our approach obviates the need for transcript annotations and circumvents the challenges in estimating relative isoform or exon usage in complex splicing events. LeafCutter can be used both to detect differential splicing between sample groups and to map splicing quantitative trait loci (sQTLs). Compared with contemporary methods, our approach identified 1.4-2.1 times more sQTLs, many of which helped us ascribe molecular effects to disease-associated variants. Transcriptome-wide associations between LeafCutter intron quantifications and 40 complex traits increased the number of associated disease genes at a 5% false discovery rate by an average of 2.1-fold compared with that detected through the use of gene expression levels alone. LeafCutter is fast, scalable, easy to use, and available online.

中文翻译：

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使用LeafCutter进行RNA拼接的无注释定量。

从pre-mRNA中切除内含子是mRNA加工中必不可少的步骤。我们开发了LeafCutter，以研究内含子剪接中的样本和种群变异。LeafCutter可从短读的RNA-seq数据中识别可变的剪接事件，并发现高度复杂的事件。我们的方法消除了对转录本注释的需要，并避免了在复杂剪接事件中估算相对同工型或外显子使用率方面的挑战。LeafCutter既可用于检测样本组之间的差异剪接，也可用于绘制剪接的定量性状位点（sQTL）。与现代方法相比，我们的方法确定的sQTL多1.4-2.1倍，其中许多有助于我们将分子效应归因于与疾病相关的变异。与仅通过基因表达水平检测到的结果相比，LeafCutter内含子定量和40个复杂性状之间的转录组范围内的关联以5％的错误发现率将相关疾病基因的数量平均提高了2.1倍。LeafCutter快速，可扩展，易于使用且可在线获得。