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ESclassifier: A random forest classifier for detection of exon skipping events from RNA-Seq data

  • School of Computer Science and Technology, Harbin Institute of Technology
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Detecting exon skipping (ES) events is an essential part in genome-wide alternative splicing event detection. In this paper, we propose a novel method ESclassifier to detect ES events from RNA-seq data. ESclassifier conducts thorough studies on predicting features and figures out proper features according to their relevance for ES event detection. Experimental results on real human heart and liver RNA-seq data show that ESclassifier could effectively filter out false positives with high predictive accuracy. The codes of ESclassifier are available at http://mlg.hit.edu.cn/ybai/ES/ESclass.html.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
EditorsHuiru Zheng, Xiaohua Tony Hu, Daniel Berrar, Yadong Wang, Werner Dubitzky, Jin-Kao Hao, Kwang-Hyun Cho, David Gilbert
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages205-208
Number of pages4
ISBN (Electronic)9781479956692
DOIs
StatePublished - 29 Dec 2014
Externally publishedYes
Event2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014 - Belfast, United Kingdom
Duration: 2 Nov 20145 Nov 2014

Publication series

NameProceedings - 2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014

Conference

Conference2014 IEEE International Conference on Bioinformatics and Biomedicine, IEEE BIBM 2014
Country/TerritoryUnited Kingdom
CityBelfast
Period2/11/145/11/14

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