Introduction

Fusion transcripts are formed by either fusion genes (DNA level) or trans-splicing events (RNA level). They have been recognized as a promising tool for diagnosing, subtyping and treating cancers. RNA-seq has become a precise and efficient standard for genome-wide screening of such aberration events. Many fusion transcript detection algorithms have been developed for paired-end RNA-seq data but their performance has not been comprehensively evaluated to guide practitioners. In this paper, we evaluated 15 popular algorithms by their precision and recall trade-off, accuracy of supporting reads and computational cost. We further combine top-performing methods for improved ensemble detection.Fifteen fusion transcript detection tools were compared using three synthetic data sets under different coverage, read length, insert size and background noise, and three real data sets with selected experimental validations. No single method dominantly performed the best but SOAPfuse generally performed well, followed by FusionCatcher and JAFFA. We further demonstrated the potential of a meta-caller algorithm by combining top performing methods to re-prioritize candidate fusion transcripts with high confidence that can be followed by experimental validation.Our result provides insightful recommendations when applying individual tool or combining top performers to identify fusion transcript candidates.

Publications

  1. Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data.
    Cite this
    Liu S, Tsai WH, Ding Y, Chen R, Fang Z, Huo Z, Kim S, Ma T, Chang TY, Priedigkeit NM, Lee AV, Luo J, Wang HW, Chung IF, Tseng GC, 2016-03-01 - Nucleic acids research

Credits

  1. Silvia Liu
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  2. Wei-Hsiang Tsai
    Developer

    Institute of Biomedical Informatics, National Yang-Ming University, Taiwan, Province of China

  3. Ying Ding
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  4. Rui Chen
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  5. Zhou Fang
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  6. Zhiguang Huo
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  7. SungHwan Kim
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  8. Tianzhou Ma
    Developer

    Department of Biostatistics, Graduate School of Public Health, United States of America

  9. Ting-Yu Chang
    Developer

    Institute of Microbiology and Immunology, National Yang-Ming University, Taiwan, Province of China

  10. Nolan Michael Priedigkeit
    Developer

    Molecular Pharmacology, School of Medicine, United States of America

  11. Adrian V Lee
    Developer

    Magee-Women's Research Institute, 204 Craft Avenue, United States of America

  12. Jianhua Luo
    Developer

    Department of Pathology, School of Medicine, United States of America

  13. Hsei-Wei Wang
    Developer

    Institute of Biomedical Informatics, National Yang-Ming University, Taiwan, Province of China

  14. I-Fang Chung
    Developer

    Institute of Biomedical Informatics, National Yang-Ming University, Taiwan, Province of China

  15. George C Tseng
    Investigator

    Department of Biostatistics, Graduate School of Public Health, United States of America

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Summary
AccessionBT006346
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByGeorge C Tseng