A Bayes regression approach to array-CGH data

Stat Appl Genet Mol Biol. 2006:5:Article3. doi: 10.2202/1544-6115.1149. Epub 2006 Feb 16.

Abstract

This paper develops a Bayes regression model having change points for the analysis of array-CGH data by utilizing not only the underlying spatial structure of the genomic alterations but also the observation that the noise associated with the ratio of the fluorescence intensities is bigger when the intensities get smaller. We show that this Bayes regression approach is particularly suitable for the analysis of cDNA microarray-CGH data, which are generally noisier than those using genomic clones. A simulation study and a real data analysis are included to illustrate this approach.

Publication types

  • Research Support, Non-U.S. Gov't
  • Validation Study

MeSH terms

  • Bayes Theorem
  • Chromosome Aberrations*
  • DNA / analysis
  • Fluorescent Dyes
  • Genomics / methods
  • Humans
  • Models, Statistical*
  • Oligonucleotide Array Sequence Analysis / methods*
  • Polymerase Chain Reaction
  • Regression Analysis

Substances

  • Fluorescent Dyes
  • DNA