EXCAVATOR: Detecting copy number variants from whole-exome sequencing data

Alberto Magi, Lorenzo Tattini, Ingrid Cifola, Romina D'Aurizio, Matteo Benelli, Eleonora Mangano, Cristina Battaglia, Elena Bonora, Ants Kurg, Marco Seri, Pamela Magini, Betti Giusti, Giovanni Romeo, Tommaso Pippucci, Gianluca De Bellis, Rosanna Abbate, Gian Franco Gensini

Research output: Contribution to journalArticle

Abstract

We developed a novel software tool, EXCAVATOR, for the detection of copy number variants (CNVs) from whole-exome sequencing data. EXCAVATOR combines a three-step normalization procedure with a novel heterogeneous hidden Markov model algorithm and a calling method that classifies genomic regions into five copy number states. We validate EXCAVATOR on three datasets and compare the results with three other methods. These analyses show that EXCAVATOR outperforms the other methods and is therefore a valuable tool for the investigation of CNVs in largescale projects, as well as in clinical research and diagnostics. EXCAVATOR is freely available at http://sourceforge.net/projects/excavatortool/.

Original languageEnglish
Article numberR120
JournalGenome Biology
Volume14
Issue number10
DOIs
Publication statusPublished - Oct 30 2013

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ASJC Scopus subject areas

  • Genetics
  • Cell Biology
  • Ecology, Evolution, Behavior and Systematics

Cite this

Magi, A., Tattini, L., Cifola, I., D'Aurizio, R., Benelli, M., Mangano, E., Battaglia, C., Bonora, E., Kurg, A., Seri, M., Magini, P., Giusti, B., Romeo, G., Pippucci, T., Bellis, G. D., Abbate, R., & Gensini, G. F. (2013). EXCAVATOR: Detecting copy number variants from whole-exome sequencing data. Genome Biology, 14(10), [R120]. https://doi.org/10.1186/gb-2013-14-10-r120