Introduction

Dispersed duplications (DDs) such as transposon element insertions and copy number variations are ubiquitous in the human genome. They have attracted the interest of biologists as well as medical researchers due to their role in both evolution and disease. The efforts of discovering DDs in high-throughput sequencing data are currently dominated by database-oriented approaches that require pre-existing knowledge of the DD elements to be detected.We present DD_DETECTION, a database-free approach to finding DD events in high-throughput sequencing data. DD_DETECTION is able to detect DDs purely from paired-end read alignments. We show in a comparative study that this method is able to compete with database-oriented approaches in recovering validated transposon insertion events. We also experimentally validate the predictions of DD_DETECTION on a human DNA sample, showing that it can find not only duplicated elements present in common databases but also DDs of novel type.The software presented in this article is open source and available from https://bitbucket.org/mkroon/dd_detection.

Publications

  1. Detecting dispersed duplications in high-throughput sequencing data using a database-free approach.
    Cite this
    Kroon M, Lameijer EW, Lakenberg N, Hehir-Kwa JY, Thung DT, Slagboom PE, Kok JN, Ye K, 2016-02-01 - Bioinformatics (Oxford, England)

Credits

  1. M Kroon
    Developer

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

  2. E W Lameijer
    Developer

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

  3. N Lakenberg
    Developer

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

  4. J Y Hehir-Kwa
    Developer

    Department of Human Genetics, Nijmegen Center for Molecular Life Sciences

  5. D T Thung
    Developer

    Department of Human Genetics, Nijmegen Center for Molecular Life Sciences

  6. P E Slagboom
    Developer

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

  7. J N Kok
    Developer

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

  8. K Ye
    Investigator

    Department of Molecular Epidemiology, Leiden University Medical Center, United States of America

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Summary
AccessionBT006637
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesC++
User InterfaceTerminal Command Line
Download Count0
Country/RegionUnited States of America
Submitted ByK Ye