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sequenceLDhot: Detecting Recombination Hotspots.

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sequenceLDhot: Detecting Recombination Hotspots. / Fearnhead, Paul.
In: Bioinformatics, Vol. 22, No. 24, 12.2006, p. 3061-3066.

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Fearnhead P. sequenceLDhot: Detecting Recombination Hotspots. Bioinformatics. 2006 Dec;22(24):3061-3066. doi: 10.1093/bioinformatics/btl540

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Fearnhead, Paul. / sequenceLDhot: Detecting Recombination Hotspots. In: Bioinformatics. 2006 ; Vol. 22, No. 24. pp. 3061-3066.

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@article{b0285180b18b47049cea1534c7f54324,
title = "sequenceLDhot: Detecting Recombination Hotspots.",
abstract = "Motivation: There is much local variation in recombination rates across the human genome—with the majority of recombination occuring in recombination hotspots—short regions of around ~2 kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, e.g. in the design and analysis of association studies for disease genes. Population genetic data, such as that generated by the HapMap project, can be used to infer the location of these hotspots. We present a new, efficient and powerful method for detecting recombination hotspots from population data. Results: We compare our method with four current methods for detecting hotspots. It is orders of magnitude quicker, and has greater power, than two related approaches. It appears to be more powerful than HotspotFisher, though less accurate at inferring the precise positions of the hotspot. It was also more powerful than LDhot in some situations: particularly for weaker hotspots (10–40 times the background rate) when SNP density is lower (< 1/kb). Availability: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.",
author = "Paul Fearnhead",
year = "2006",
month = dec,
doi = "10.1093/bioinformatics/btl540",
language = "English",
volume = "22",
pages = "3061--3066",
journal = "Bioinformatics",
issn = "1460-2059",
publisher = "Oxford University Press",
number = "24",

}

RIS

TY - JOUR

T1 - sequenceLDhot: Detecting Recombination Hotspots.

AU - Fearnhead, Paul

PY - 2006/12

Y1 - 2006/12

N2 - Motivation: There is much local variation in recombination rates across the human genome—with the majority of recombination occuring in recombination hotspots—short regions of around ~2 kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, e.g. in the design and analysis of association studies for disease genes. Population genetic data, such as that generated by the HapMap project, can be used to infer the location of these hotspots. We present a new, efficient and powerful method for detecting recombination hotspots from population data. Results: We compare our method with four current methods for detecting hotspots. It is orders of magnitude quicker, and has greater power, than two related approaches. It appears to be more powerful than HotspotFisher, though less accurate at inferring the precise positions of the hotspot. It was also more powerful than LDhot in some situations: particularly for weaker hotspots (10–40 times the background rate) when SNP density is lower (< 1/kb). Availability: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.

AB - Motivation: There is much local variation in recombination rates across the human genome—with the majority of recombination occuring in recombination hotspots—short regions of around ~2 kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, e.g. in the design and analysis of association studies for disease genes. Population genetic data, such as that generated by the HapMap project, can be used to infer the location of these hotspots. We present a new, efficient and powerful method for detecting recombination hotspots from population data. Results: We compare our method with four current methods for detecting hotspots. It is orders of magnitude quicker, and has greater power, than two related approaches. It appears to be more powerful than HotspotFisher, though less accurate at inferring the precise positions of the hotspot. It was also more powerful than LDhot in some situations: particularly for weaker hotspots (10–40 times the background rate) when SNP density is lower (< 1/kb). Availability: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.

U2 - 10.1093/bioinformatics/btl540

DO - 10.1093/bioinformatics/btl540

M3 - Journal article

VL - 22

SP - 3061

EP - 3066

JO - Bioinformatics

JF - Bioinformatics

SN - 1460-2059

IS - 24

ER -