BioHMM:: a heterogeneous hidden Markov model for segmenting array CGH data

被引:102
作者
Marioni, JC
Thorne, NP
Tavaré, S
机构
[1] Univ Cambridge, Hutchison MRC Res Ctr, Dept Oncol, Computat Biol Grp, Cambridge CB2 1TN, England
[2] Univ Cambridge, Dept Appl Math & Theoret Phys, Cambridge CB2 1TN, England
关键词
D O I
10.1093/bioinformatics/btl089
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
We have developed a new method (BioHMM) for segmenting array comparative genomic hybridization data into states with the same underlying copy number. By utilizing a heterogeneous hidden Markov model, BioHMM incorporates relevant biological factors (e.g. the distance between adjacent clones) in the segmentation process.
引用
收藏
页码:1144 / 1146
页数:3
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