A new method for detecting human recombination hotspots and its applications to the HapMap ENCODE data

Li, J., Zhang, M. Q., Zhang, X. (2006) A new method for detecting human recombination hotspots and its applications to the HapMap ENCODE data. American Journal of Human Genetics, 79 (4). pp. 628-639. ISSN 00029297

URL: https://www.ncbi.nlm.nih.gov/pubmed/16960799
DOI: 10.1086/508066

Abstract

Computational detection of recombination hotspots from population polymorphism data is important both for understanding the nature of recombination and for applications such as association studies. We propose a new method for this task based on a multiple-hotspot model and an (approximate) log-likelihood ratio test. A truncated, weighted pairwise log-likelihood is introduced and applied to the calculation of the log-likelihood ratio, and a forward-selection procedure is adopted to search for the optimal hotspot predictions. The method shows a relatively high power with a low false-positive rate in detecting multiple hotspots in simulation data and has a performance comparable to the best results of leading computational methods in experimental data for which recombination hotspots have been characterized by sperm-typing experiments. The method can be applied to both phased and unphased data directly, with a very fast computational speed. We applied the method to the 10 500-kb regions of the HapMap ENCODE data and found 172 hotspots among the three populations, with average hotspot width of 2.4 kb. By comparisons with the simulation data, we found some evidence that hotspots are not all identical across populations. The correlations between detected hotspots and several genomic characteristics were examined. In particular, we observed that DNaseI-hypersensitive sites are enriched in hotspots, suggesting the existence of human ? hotspots similar to those found in yeast. © 2006 by The American Society of Human Genetics. All rights reserved.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > enzymes > DNAse
bioinformatics > genomics and proteomics > databases > database optimization
bioinformatics > genomics and proteomics > databases
bioinformatics > computational biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > recombination
CSHL Authors:
Communities: CSHL labs > Zhang lab
Depositing User: CSHL Librarian
Date Deposited: 12 Dec 2011 16:34
Last Modified: 19 Apr 2018 15:55
PMCID: PMC1592557
Related URLs:
URI: http://repository.cshl.edu/id/eprint/22851

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