Population-based change-point detection for the identification of homozygosity islands.

ABSTRACT:

Motivation

This work is motivated by the problem of identifying homozygosity islands on the genome of individuals in a population. Our method directly tackles the issue of identification of the homozygosity islands at the population level, without the need of analysing single individuals and then combine the results, as is made nowadays in state-of-the-art approaches.

Results

We propose regularized offline change-point methods to detect changes in the parameters of a multidimensional distribution when we have several aligned, independent samples of fixed resolution. We present a penalized maximum likelihood approach that can be efficiently computed by a dynamic programming algorithm or approximated by a fast binary segmentation algorithm. Both estimators are shown to converg

SUBMITTER: Prates L 

PROVIDER: S-EPMC10112956 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature