Detecting genomic aberrations using products in a multiscale analysis.
Genomic instability, such as copy-number losses and gains, occurs in many genetic diseases. Recent technology developments enable researchers to measure copy numbers at tens of thousands of markers simultaneously. In this article, we propose a nonparametric approach for detecting the locations of copy-number changes and provide a measure of significance for each change point. The proposed test is based on seeking scale-based changes in the sequence of copy numbers, which is ordered by the marker locations along the chromosome. The method leads to a natural way to estimate the null distribution for the test of a change point and adjusted p-values for the significance of a change point using a step-down maxT permutation algorithm to control the family-wise error rate. A simulation study investigates the finite sample performance of the proposed method and compares it with a more standard sequential testing method. The method is illustrated using two real data sets.
Yu
Xuesong
X
Statistical Center for HIV/AIDS Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA. xyu@fhcrc.org
Randolph
Timothy W
TW
Tang
Hua
H
Hsu
Li
L
D000465:Algorithms; D001699:Biometry / Q000379:methods; D018628:Gene Dosage; D005819:Genetic Markers; D016678:Genome; D042822:Genomic Instability; D008722:Methods
D005819:Genetic Markers