Title: Multi-sequence segmentation via score and higher-criticism tests,
Abstract: We propose local segmentation of multiple sequences sharing a common time- or
location-index, building upon the single sequence local segmentation methods of
Niu and Zhang (2012) and Fang, Li and Siegmund (2016). We also propose reverse
segmentation of multiple sequences that is new even in the single sequence
context. We show that local segmentation estimates change-points consistently
for both single and multiple sequences, and that both methods proposed here
detect signals well, with the reverse segmentation method outperforming a large
number of known segmentation methods on a commonly used single sequence test
scenario. We show that on a recent allele-specific copy number study involving
multiple cancer patients, the simultaneous segmentations of the DNA sequences
of all the patients provide information beyond that obtained by segmentation of
the sequences one at a time.