Introduction

Copy number variations are important in the detection and progression of significant tumors and diseases. Recently, Whole Exome Sequencing is gaining popularity with copy number variations detection due to low cost and better efficiency. In this work, we developed VEGAWES for accurate and robust detection of copy number variations on WES data. VEGAWES is an extension to a variational based segmentation algorithm, VEGA: Variational estimator for genomic aberrations, which has previously outperformed several algorithms on segmenting array comparative genomic hybridization data.We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. The results on the real data were analyzed with segmentation obtained from Single-nucleotide polymorphism data as ground truth. We compared our results with two other segmentation algorithms and assessed the performance based on accuracy and time.In terms of both accuracy and time, VEGAWES provided better results on the synthetic data and tumor samples demonstrating its potential in robust detection of aberrant regions in the genome.

Publications

  1. VEGAWES: variational segmentation on whole exome sequencing for copy number detection.
    Cite this
    Anjum S, Morganella S, D'Angelo F, Iavarone A, Ceccarelli M, 2015-09-01 - BMC bioinformatics

Credits

  1. Samreen Anjum
    Developer

    Computational Sciences and Engineering, Qatar Computing Research Institute

  2. Sandro Morganella
    Developer

    European Molecular Biology Laboratory, European Bioinformatics Institute

  3. Fulvio D'Angelo
    Developer

    BIOGEM, Ariano Irpino

  4. Antonio Iavarone
    Developer

    Institute for Cancer Genetics, Columbia University

  5. Michele Ceccarelli
    Investigator

    Department of Science and Technology, University of Sannio

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Summary
AccessionBT006727
Tool TypeApplication
Category
PlatformsLinux/Unix
TechnologiesR
User InterfaceTerminal Command Line
Download Count0
Submitted ByMichele Ceccarelli