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Bioinformatics Advance Access published online on October 23, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl540
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received August 4, 2006
Revised September 25, 2006
Accepted October 17, 2006

Article

SequenceLDhot: detecting recombination hotspots

Paul Fearnhead 1 *

1 Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, UK

* To whom correspondence should be addressed.
Paul Fearnhead, E-mail: p.fearnhead{at}lancs.ac.uk


  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 2kb in length that have much higher recombination rates than neighbouring regions. Knowledge of this local variation is important, for example 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 (less than 1 per kb).

Availability: Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.

Associate Editor: Martin Bishop
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