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A Comparison of Computational Approaches for Intron Retention Detection
内含子保留检测计算方法的比较
イントロン保持検出のための計算アプローチの比較
인트론 잔류 검출을 위한 전산 접근 방식의 비교
Una comparación de enfoques computacionales para la detección de retención de intrones
Comparaison des approches informatiques pour la détection de la rétention d'intron
Сравнение вычислительных подходов к обнаружению удержания интронов
Jiantao Zheng 郑剑涛, Cuixiang Lin 林翠香, Zhenpeng Wu 伍振鹏, Hong-Dong Li 李洪东
Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China
中国 长沙 中南大学计算机学院 生物信息学湖南省重点实验室
Big Data Mining and Analytics, 19 January 2022
Abstract

Intron Retention (IR) is an alternative splicing mode through which introns are retained in mature RNAs rather than being spliced in most cases. IR has been gaining increasing attention in recent years because of its recognized association with gene expression regulation and complex diseases. Continuous efforts have been dedicated to the development of IR detection methods.

These methods differ in their metrics to quantify retention propensity, performance to detect IR events, functional enrichment of detected IRs, and computational speed. A systematic experimental comparison would be valuable to the selection and use of existing methods. In this work, we conduct an experimental comparison of existing IR detection methods. Considering the unavailability of a gold standard dataset of intron retention, we compare the IR detection performance on simulation datasets. Then, we compare the IR detection results with real RNA-Seq data.

We also describe the use of differential analysis methods to identify disease-associated IRs and compare differential IRs along with their Gene Ontology enrichment, which is illustrated on an Alzheimer's disease RNA-Seq dataset. We discuss key principles and features of existing approaches and outline their differences. This systematic analysis provides helpful guidance for interrogating transcriptomic data from the point of view of IR.
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