Systematic analysis of alternative splicing in time course data using Spycone

Abstract

During disease progression or organism development, alternative splicing (AS) may lead to isoform switches (IS) that demonstrate similar temporal patterns and reflect the AS co-regulation of such genes. Tools for dynamic process analysis usually neglect AS. Here we propose Spycone (https://github.com/yollct/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.

Publication
bioRxiv
Chit Tong Lio
Chit Tong Lio
PhD student
Zakaria Louadi
Zakaria Louadi
PhD student
Amit Fenn
Amit Fenn
PhD student
Olga Tsoy
Olga Tsoy
Group Leader

I’m a group leader of Computational Genomics and Transcriptomics group. I focus on the BMBF funded Sys_CARE project about alternative splicing in cardiac and renal diseases. I graduated from Lomonosov Moscow State University and did PhD in Kharkevich Institute in Moscow at professor Gelfand lab. There I studied the evolution of transcriptional regulatory networks in bacteria. During my PhD I shortly stayed at Stowers Institute for Medical Research, Kansas-City, where I went on working on regulation of bacterial metabolic pathways. As a research scientist, I worked in Skolkovo Institute of Science and Technology, Moscow on 3D chromatin structure analysis.