A computational method to predict DNA copy number alterations from gene expression data in tumor cases

Huimin Geng, Wing C. Chan, Hesham H. Ali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Genetic alterations, such as chromosomal gains and losses, are key causes of tumorigenesis. Comparative Genomic Hybridization (CGH) is a molecular method for detecting such DNA copy number alterations in tumor cells. Recent observations have reported that in many tumors, the mRNA transcript changes measured by gene expression profiling (GEP) are correlated with corresponding DNA copy number alterations, supporting the possibility of predicting DNA copy number alterations from GEP data. In this paper, contrary to the traditional use of GEP, we present a new analytical approach utilizing GEP data for predicting DNA copy number alterations. The proposed approach is built on a hidden Markov model and trained in the light of paired GEP and CGH data on a sufficient number of tumor cases of the same tumor type. Then it can be applied to new cases of that tumor type to predict the CGH profiles from their GEP profiles.

Original languageEnglish (US)
Title of host publicationProceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS
DOIs
StatePublished - 2009
Event42nd Annual Hawaii International Conference on System Sciences, HICSS - Waikoloa, HI, United States
Duration: Jan 5 2009Jan 9 2009

Publication series

NameProceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS

Conference

Conference42nd Annual Hawaii International Conference on System Sciences, HICSS
CountryUnited States
CityWaikoloa, HI
Period1/5/091/9/09

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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