Spatial smoothing and hot spot detection for CGH data using the fused lasso. (English) Zbl 1274.62886

Tibshirani, Robert; Wang, Pei

Biostatistics 9, No. 1, 18-29 (2008).

Summary: We apply the “fused lasso” regression method to the problem of “hot-spot 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.

MSC:

62P10	Applications of statistics to biology and medical sciences; meta analysis
62J07	Ridge regression; shrinkage estimators (Lasso)
65C60	Computational problems in statistics (MSC2010)

Keywords:

DNA copy number; signal detection

Software:

SQOPT; SemiPar