Whole-genome CNV analysis: Advances in computational approaches

Mehdi Pirooznia, Fernando Goes, Peter P. Zandi

Research output: Contribution to journalArticlepeer-review

Abstract

Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing (NGS) data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development.

Original languageEnglish (US)
Article number138
JournalFrontiers in Genetics
Volume6
Issue numberMAR
DOIs
StatePublished - Jan 1 2015

ASJC Scopus subject areas

  • Molecular Medicine
  • Genetics
  • Genetics(clinical)

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