Spatial smoothing and hot spot detection for CGH data using the fused lasso

被引：244

作者：

Tibshirani, Robert ^{[1
,2
]}

Wang, Pei ^{[3
]}

机构：

[1] Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA

[2] Stanford Univ, Dept Biostat, Stanford, CA 94305 USA

[3] Fred Hutchinson Canc Res Ctr, Seattle, WA 98109 USA

来源：

BIOSTATISTICS | 2008年 / 9卷 / 01期

关键词：

DNA copy number; Signal detection;

D O I：

10.1093/biostatistics/kxm013

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We apply the "fused lasso" regression method of Tibshirani and others (2004) to the problem of "hotspot detection", in particular, detection of regions of gain or loss in comparative genomic hybridization (CGH) data. The fused lasso criterion leads to a convex optimization problem, and we provide a fast algorithm for its solution. Estimates of false-discovery rate are also provided. Our studies show that the new method generally outperforms competing methods for calling gains and losses in CGH data.

引用

页码：18 / 29

页数：12

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