ASpli: integrative analysis of splicing landscapes through RNA-Seq assays
ASpli: integrative analysis of splicing landscapes through RNA-Seq assays
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DOI：
10.1093/bioinformatics/btab141
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发表时间：
2021-03-02
期刊：
影响因子：
5.8
通讯作者：
Chernomoretz, Ariel
中科院分区：
文献类型：
--
作者：
Mancini, Estefania;Rabinovich, Andres;Chernomoretz, Ariel
动机：自下一代测序技术的早期以来，选择性剪接的全基因组分析一直是一个非常活跃的研究领域。从那时起，不断增长的数据可用性和日益复杂的分析方法的发展揭示了一般拼接库的复杂性。存在大量的剪接分析方法，每种方法都有自己的优点和缺点。例如，完全依赖于连接信息的方法不能利用 RNA-seq 测定中产生的绝大多数读数，异构体重建方法可能无法检测新的内含子保留事件，一些解决方案只能处理规范剪接事件，并且许多现有方法只能执行成对比较。 结果：在本贡献中，我们提出了 ASpli，这是一个用 R 统计语言实现的计算套件，它允许识别带注释的和新颖的选择性剪接事件中的变化，并且可以处理简单的、多因素或配对实验设计。我们的综合计算工作流程考虑将相同的 GLM 模型应用于不同的读取和连接集，从而允许计算互补剪接信号。分析模拟数据和真实数据，我们发现这些信号的合并产生了剪接改变发生的稳健代理。虽然对连接点的分析使我们能够发现带注释和未注释的事件，但与其他最先进的剪接分析算法相比，读取覆盖率信号显着提高了召回能力，并且性能非常有竞争力。
Motivation: Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons.Results: In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals. Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as nonannotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms.