Detecting Genomic Aberrations Using Products in a Multiscale Analysis

Summary 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.