Next-generation RNA sequencing allows alternative splicing (AS) quantification with unprecedented resolution, with the relative inclusion of an alternative sequence in transcripts being commonly quantified by the proportion of reads supporting it as percent spliced-in (PSI). However, PSI values do not incorporate information about precision, proportional to the respective AS events’ read coverage. Beta distributions are suitable to quantify inclusion levels of alternative sequences, using reads supporting their inclusion and exclusion as surrogates for the two distribution shape parameters. Each such beta distribution has the PSI as its mean value and is narrower when the read coverage is higher, facilitating the interpretability of its precision when plotted. We herein introduce a computational pipeline, based on beta distributions accurately modeling PSI values and their precision, to quantitatively and visually compare AS between groups of samples. Our methodology includes a differential splicing significance metric that compromises the magnitude of intergroup differences, the estimation uncertainty in individual samples, and the intragroup variability, being therefore suitable for multiple-group comparisons. To make our approach accessible and clear to both noncomputational and computational biologists, we developed betAS, an interactive web app and user-friendly R package for visual and intuitive differential splicing analysis from read count data.

中文翻译：

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betAS：使用 beta 分布对差异选择性剪接进行直观分析和可视化

下一代 RNA 测序允许以前所未有的分辨率对选择性剪接 (AS) 进行定量，转录本中选择性剪接的相对包含情况通常通过支持其剪接百分比 (PSI) 的读数比例来量化。然而，PSI 值不包含有关精度的信息，与相应 AS 事件的读取覆盖率成比例。Beta 分布适合量化替代序列的包含水平，使用支持其包含和排除的读数作为两个分布形状参数的替代。每个这样的 beta 分布都以 PSI 作为其平均值，并且当读取覆盖率较高时更窄，从而有助于绘制时其精度的可解释性。我们在此引入了一个计算管道，基于 beta 分布，准确地模拟 PSI 值及其精度，以定量和直观地比较样本组之间的 AS。我们的方法包括差异剪接显着性指标，该指标折衷了组间差异的大小、个体样本的估计不确定性以及组内变异性，因此适合多组比较。为了使非计算生物学家和计算生物学家都能理解和理解我们的方法，我们开发了 betAS，这是一个交互式网络应用程序和用户友好的 R 包，用于根据读数计数数据进行可视化和直观的差异剪接分析。