Systematic analysis of alternative splicing in time course data using Spycone.

ABSTRACT:

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 https://github.co

SUBMITTER: Lio CT 

PROVIDER: S-EPMC9831059 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature