Systematic analysis of alternative splicing in time course data using Spycone

Chit Tong Lio, Gordon Grabert, Zakaria Louadi, Amit Fenn, Jan Baumbach, Tim Kacprowski, Markus List, Olga Tsoy

Research output: Contribution to journalJournal articleResearchpeer-review

3 Downloads (Pure)


MOTIVATION: During disease progression or organism development, alternative splicing may lead to isoform switches that demonstrate similar temporal patterns and reflect the alternative splicing co-regulation of such genes. Tools for dynamic process analysis usually neglect alternative splicing. RESULTS: Here, we propose Spycone, a splicing-aware framework for time course data analysis. Spycone exploits a novel IS detection algorithm and offers downstream analysis such as network and gene set enrichment. We demonstrate the performance of Spycone using simulated and real-world data of SARS-CoV-2 infection. AVAILABILITY AND IMPLEMENTATION: The Spycone package is available as a PyPI package. The source code of Spycone is available under the GPLv3 license at and the documentation at SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish
Article numberbtac846
JournalBioinformatics (Oxford, England)
Issue number1
Number of pages9
Publication statusPublished - Jan 2023


Dive into the research topics of 'Systematic analysis of alternative splicing in time course data using Spycone'. Together they form a unique fingerprint.

Cite this