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ESGq: Alternative Splicing events quantification across conditions based on Event Splicing Graphs

Authors :
Brejová, B
Ciencialová, L
Holeňa, M
Jajcay, R
Jajcayová, T
Lexa, M
Mráz, F
Pardubská, D
Plátek, M
Cozzi, D
Bonizzoni, P
Denti, L
Cozzi D.
Bonizzoni P.
Denti L.
Brejová, B
Ciencialová, L
Holeňa, M
Jajcay, R
Jajcayová, T
Lexa, M
Mráz, F
Pardubská, D
Plátek, M
Cozzi, D
Bonizzoni, P
Denti, L
Cozzi D.
Bonizzoni P.
Denti L.
Publication Year :
2023

Abstract

Alternative Splicing (AS) is a regulation mechanism that contributes to protein diversity and is also associated to many diseases and tumors. Alternative splicing events quantification from RNA-Seq reads is a crucial step in understanding this complex biological mechanism. However, tools for AS events detection and quantification show inconsistent results. This reduces their reliability in fully capturing and explaining alternative splicing. We introduce ESGq, a novel approach for the quantification of AS events across conditions based on read alignment against Event Splicing Graphs. By comparing ESGq to two state-of-the-art tools on real RNA-Seq data, we validate its performance and evaluate the statistical correlation of the results. ESGq is freely available at https://github.com/AlgoLab/ESGq.

Details

Database :
OAIster
Notes :
English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1427427061
Document Type :
Electronic Resource