isopretgo -分析和可视化差异剪接的功能后果。

IF 4 Q1 GENETICS & HEREDITY
NAR Genomics and Bioinformatics Pub Date : 2024-12-05 eCollection Date: 2024-12-01 DOI:10.1093/nargab/lqae165
Guy Karlebach, Peter Hansen, Kristin Köhler, Peter N Robinson
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引用次数: 0

摘要

基因本体过表示分析(GO-ORA)是RNA测序(RNA-seq)实验中表征差异表达基因(DGE)组显著功能特征的标准方法。GO- ora将DGE的GO注释分布与所有基因或所有表达基因的GO注释分布进行比较。这种方法还不能用于表征差异选择性剪接(DAS)。在这里,我们介绍了一个名为isopretGO的桌面应用程序,用于可视化DGE和DAS的功能含义,该应用程序利用了我们之前发布的对单个同种异构体GO注释的机器学习预测。基于对100个RNA-seq数据集的分析,我们发现DAS和DGE通常具有截然不同的功能谱。我们提出了一个例子,表明如何使用isopretGO来识别可归因于差异剪接的RNA-seq数据中的功能变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IsopretGO-analysing and visualizing the functional consequences of differential splicing.

Gene Ontology overrepresentation analysis (GO-ORA) is a standard approach towards characterizing salient functional characteristics of sets of differentially expressed genes (DGE) in RNA sequencing (RNA-seq) experiments. GO-ORA compares the distribution of GO annotations of the DGE to that of all genes or all expressed genes. This approach has not been available to characterize differential alternative splicing (DAS). Here, we introduce a desktop application called isopretGO for visualizing the functional implications of DGE and DAS that leverages our previously published machine-learning predictions of GO annotations for individual isoforms. We show based on an analysis of 100 RNA-seq datasets that DAS and DGE frequently have starkly different functional profiles. We present an example that shows how isopretGO can be used to identify functional shifts in RNA-seq data that can be attributed to differential splicing.

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来源期刊
CiteScore
8.00
自引率
2.20%
发文量
95
审稿时长
15 weeks
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