title: SequenceLDhot: detecting recombination hotspots.
abstract: BACKGROUND
  There is much local variation in recombination rates across the human genome--with the majority of recombination occurring in recombination hotspots--short regions of around approximately 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).
  
  
  BACKGROUND
  Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.
authors.affiliation: Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, UK. p.fearnhead@lancs.ac.uk
authors.forename: Paul
authors.initials: P
authors.lastname: Fearnhead
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D002874:Chromosome Mapping / Q000379:methods*; D030541:Databases, Genetic; D005828:Genetics, Population; D008969:Molecular Sequence Data; D011110:Polymorphism, Genetic; D011995:Recombination, Genetic / Q000235:genetics*; D017422:Sequence Analysis, DNA / Q000379:methods*; D012984:Software