Bayesian joint estimation of CN and LOH aberrations

Paola M V Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee

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

Abstract

SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages1109-1117
Number of pages9
Volume5518 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2009
Event10th International Work-Conference on Artificial Neural Networks, IWANN 2009 - Salamanca, Spain
Duration: Jun 10 2009Jun 12 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5518 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other10th International Work-Conference on Artificial Neural Networks, IWANN 2009
CountrySpain
CitySalamanca
Period6/10/096/12/09

Keywords

  • Bayesian regression
  • Change point problem
  • DNA copy number estimation
  • LOH estimation
  • Piecewise constant function

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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