Journal
JOURNAL OF MULTIVARIATE ANALYSIS
Volume 165, Issue -, Pages 143-165Publisher
ELSEVIER INC
DOI: 10.1016/j.jmva.2017.12.005
Keywords
Hi-C data; Multiple change-point estimation; Nonparametric estimation
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Funding
- Agence nationale de la recherche (ANR) [ANR-11-BINF-0001-06]
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We propose a novel nonparametric approach to estimate the location of block boundaries (change-points) of non-overlapping blocks in a random symmetric matrix which consists of random variables whose distribution changes from block to block. Our change-point location estimators are based on nonparametric homogeneity tests for matrices. We first provide some theoretical results for these tests. Then, we prove the consistency of our change-point location estimators. Some numerical experiments are also provided in order to support our claims. Finally, our approach is applied to Hi-C data which are used in molecular biology to study the influence of chromosomal conformation on cell function. (C) 2017 Elsevier Inc. All rights reserved.
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