Robust Composite Interval Mapping for QTL Analysis by Minimum beta-Divergence Method

Author

Mollah, Md Nurul Haque ; Eguchi, Shinto

Author_Institution

Inst. of Stat. Math., Tokyo

fYear

2008

fDate

3-5 Nov. 2008

Firstpage

115

Lastpage

120

Abstract

Interval mapping (IM) is currently the most popular approach for quantitative trait loci (QTL) analysis in experimental crosses.Composite interval mapping (CIM) is a generalized version of interval mapping. However, the traditional IM and CIM approaches both are sensitive to outliers. This paper discusses a new robust CIM algorithm for QTL mapping in an experimental organisms by minimizing beta-divergence using the EM algorithm. Simulation studies show that the proposed method significantly improves the performance over the traditional CIM method for QTL mapping in presence of outliers; otherwise, it keeps equal performance.

Keywords

Gaussian distribution; biology computing; genetics; physiological models; EM algorithm; QTL analysis; interval mapping; minimum beta-divergence method; quantitative trait loci; Algorithm design and analysis; Bioinformatics; Computer integrated manufacturing; Frequency; Genetics; Mathematics; Organisms; Robustness; Statistical analysis; Testing; Composite interval mapping (CIM); Gaussian mixture distribution; Quantitative trait loci (QTL);

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine, 2008. BIBM '08. IEEE International Conference on

Conference_Location

Philadelphia, PA

Print_ISBN

978-0-7695-3452-7

Type

conf

DOI

10.1109/BIBM.2008.43

Filename

4684881