title: ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  ExomeAI is a web-based application, publicly available at: http://genomequebec.mcgill.ca/exomeai.
  
  
  BACKGROUND
  JavadNadaf@gmail.com or somayyeh.fahiminiya@mcgill.ca
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.
authors.forename: Javad
authors.initials: J
authors.lastname: Nadaf
authors.affiliation: Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.
authors.forename: Jacek
authors.initials: J
authors.lastname: Majewski
authors.affiliation: Department of Human Genetics, Faculty of Medicine, McGill University and Genome Quebec Innovation Center, Montreal, Quebec, Canada.
authors.forename: Somayyeh
authors.initials: S
authors.lastname: Fahiminiya
mesh_terms: D022981:Allelic Imbalance / Q000235:genetics*; D003198:Computer Simulation; D059472:Exome / Q000235:genetics*; D015894:Genome, Human / Q000235:genetics*; D006579:Heterozygote; D006801:Humans; D019656:Loss of Heterozygosity; D009369:Neoplasms / Q000175:diagnosis / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software