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Article Dans Une Revue Bioinformatics Année : 2014

Two-dimensional segmentation for analyzing Hi-C data

Celine Lévy-Leduc
  • Fonction : Auteur
Maud Delattre
T. Mary-Huard
  • Fonction : Auteur

Résumé

Abstract Motivation: The spatial conformation of the chromosome has a deep influence on gene regulation and expression. Hi-C technology allows the evaluation of the spatial proximity between any pair of loci along the genome. It results in a data matrix where blocks corresponding to (self-)interacting regions appear. The delimitation of such blocks is critical to better understand the spatial organization of the chromatin. From a computational point of view, it results in a 2D segmentation problem. Results: We focus on the detection of cis-interacting regions, which appear to be prominent in observed data. We define a block-wise segmentation model for the detection of such regions. We prove that the maximization of the likelihood with respect to the block boundaries can be rephrased in terms of a 1D segmentation problem, for which the standard dynamic programming applies. The performance of the proposed methods is assessed by a simulation study on both synthetic and resampled data. A comparative study on public data shows good concordance with biologically confirmed regions. Availability and implementation: The HiCseg R package is available from the Comprehensive R Archive Network and from the Web page of the corresponding author. Contact: celine.levy-leduc@agroparistech.fr

Dates et versions

hal-04083798 , version 1 (27-04-2023)

Identifiants

Citer

Celine Lévy-Leduc, Maud Delattre, T. Mary-Huard, S. Robin. Two-dimensional segmentation for analyzing Hi-C data. Bioinformatics, 2014, 30 (17), pp.i386-i392. ⟨10.1093/bioinformatics/btu443⟩. ⟨hal-04083798⟩
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