Analysing DNA copy number changes using fused margin regression

Yuanjian Feng, Guoqiang Yu, Tian Li Wang, Ie Ming Shih, Yue Wang

Research output: Contribution to journalArticle

Abstract

DNA copy number change is an important form of structural variations in human genomes. Detecting copy number changes using DNA array data is a challenging task due to high density genomic loci, low signal to noise ratios, and normal tissue contamination. We propose Fused Margin Regression (FMR) method that combines a variable fusion rule and robust ε-insensitive loss criterion to estimate piecewise constant segments of the underlying copy number profile. We tested FMR method on both simulation and real CGH and SNP array datasets, and observed competitively improved performance as compared to several widely-adopted existing methods.

Original languageEnglish (US)
Pages (from-to)3-15
Number of pages13
JournalInternational Journal of Functional Informatics and Personalised Medicine
Volume3
Issue number1
DOIs
StatePublished - Jan 1 2010

Keywords

  • CGH copy number
  • DNA copy number change detection
  • FMR
  • Fused margin regression
  • L1-norm regularisation
  • Regularised regression
  • SNP copy number
  • SVR
  • Segmentation
  • Support vector regression
  • Variable fusion

ASJC Scopus subject areas

  • Clinical Neurology

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