Systematic analysis of alternative splicing in time course data using Spycone

Spycone is available as a python package that provides systematic analysis of time course transcriptomics data. Figure 1 shows the workflow of Spycone. It uses gene or isoform expression and a biological network as an input. It employs the sum of changes of all isoforms relative abundance (total isoform usage) across time points to detect IS events. It further provides downstream analysis such as clustering by total isoform usage, gene set enrichment analysis, network enrichment, and splicing factors analysis. The SARS-Cov-2 infection and cancer dataset are used as an application demonstration for our Spycone tool and a simulation dataset is used for benchmark analysis.Spycone 是一款Python软件包，可用于对时间序列转录组学数据（time course transcriptomics data）进行系统化分析。图1展示了Spycone的分析流程。该工具以基因或转录本异构体（isoform）表达量以及生物网络作为输入，利用所有转录本异构体在各时间点的相对丰度变化总和（即总转录本使用量，total isoform usage）来检测IS事件。此外，Spycone还提供多项下游分析功能，包括基于总转录本使用量的聚类分析、基因集富集分析（gene set enrichment analysis）、网络富集分析以及剪接因子分析。本研究以新冠病毒感染（SARS-CoV-2 infection）数据集与癌症数据集作为Spycone工具的应用演示案例，并采用模拟数据集开展基准测试分析。