利用群体遗传数据识别重组热点
Identifying recombination hotspots using population genetic data
摘要：
动机：重组率在哺乳动物基因组内的精细尺度上变化很大，大多数重组发生在宽度约2 kb的热点内。我们提出了一种从群体遗传数据样本中的连锁不平衡模式推断重组热点位置的方法。结果如下：使用模拟，我们表明，我们的方法具有约50- 60%的热点检测能力，但取决于热点的大小。对于典型的人类数据，假阳性率在0.24和0.56假阳性/Mb之间。可用性：http://github.com/auton1/LDhot
英文摘要：
Motivation: Recombination rates vary considerably at the fine scale within mammalian genomes, with the majority of recombination occurring within hotspots of ~2 kb in width. We present a method for inferring the location of recombination hotspots from patterns of linkage disequilibrium within samples of population genetic data. Results: Using simulations, we show that our method has hotspot detection power of approximately 50-60%, but depending on the magnitude of the hotspot. The false positive rate is between 0.24 and 0.56 false positives per Mb for data typical of humans. Availability: http://github.com/auton1/LDhot
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