ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data

Bioinformatics. 2015 Feb 1;31(3):429-31. doi: 10.1093/bioinformatics/btu665. Epub 2014 Oct 8.

Abstract

Summary: Whole-exome sequencing (WES) has extensively been used in cancer genome studies; however, the use of WES data in the study of loss of heterozygosity or more generally allelic imbalance (AI) has so far been very limited, which highlights the need for user-friendly and flexible software that can handle low-quality datasets. We have developed a statistical approach, ExomeAI, for the detection of recurrent AI events using WES datasets, specifically where matched normal samples are not available.

Availability: ExomeAI is a web-based application, publicly available at: http://genomequebec.mcgill.ca/exomeai.

Contact: JavadNadaf@gmail.com or somayyeh.fahiminiya@mcgill.ca

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Allelic Imbalance / genetics*
  • Computer Simulation
  • Exome / genetics*
  • Genome, Human / genetics*
  • Heterozygote
  • Humans
  • Loss of Heterozygosity
  • Neoplasms / diagnosis
  • Neoplasms / genetics*
  • Sequence Analysis, DNA / methods*
  • Software*