Fearnhead Paul
Department of Mathematics and Statistics, Lancaster University, Lancaster LA1 4YF, UK.
Bioinformatics. 2006 Dec 15;22(24):3061-6. doi: 10.1093/bioinformatics/btl540. Epub 2006 Oct 23.
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.
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).
Program, data sets, and full details of results are available at: http://www.maths.lancs.ac.uk/~fearnhea/Hotspot.
人类基因组中重组率存在很大的局部差异——大多数重组发生在重组热点区域,即长度约为2 kb的短区域,其重组率远高于相邻区域。了解这种局部差异很重要,例如在疾病基因关联研究的设计和分析中。群体遗传数据,如国际人类基因组单体型图计划(HapMap项目)产生的数据,可用于推断这些热点区域的位置。我们提出了一种从群体数据中检测重组热点的新方法,该方法高效且强大。
我们将我们的方法与当前四种检测热点的方法进行了比较。它比两种相关方法快几个数量级,且检测能力更强。它似乎比HotspotFisher更具检测能力,尽管在推断热点的精确位置时准确性稍差。在某些情况下,它也比LDhot更具检测能力:特别是对于较弱的热点(背景率的10 - 40倍),当单核苷酸多态性(SNP)密度较低(< 1/kb)时。
程序、数据集及结果的完整详细信息可在以下网址获取:http://www.maths.lancs.ac.uk/~fearnhea/Hotspot 。