کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7546672 | 1489635 | 2018 | 23 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Nonparametric multiple change-point estimation for analyzing large Hi-C data matrices
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موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آنالیز عددی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Nonparametric multiple change-point estimation for analyzing large Hi-C data matrices Nonparametric multiple change-point estimation for analyzing large Hi-C data matrices](/preview/png/7546672.png)
چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Multivariate Analysis - Volume 165, May 2018, Pages 143-165
Journal: Journal of Multivariate Analysis - Volume 165, May 2018, Pages 143-165
نویسندگان
Vincent Brault, Sarah Ouadah, Laure Sansonnet, Céline Lévy-Leduc,