To demonstrate the utility of our recombination detection method we conducted association testing between genetic variants in the PRDM9 region (chr5:23007723–24028706) and the “hotspot usage” phenotype described in Coop et al. (2008) [39] (link). Substantial association in this region was also found in Kong et al. (2010) [12] (link) and Hinch (2011) [41] (link). We calculated the same phenotype as Coop et al. (2008), the proportion of crossover events, , that occur in a recombination hotspot for individual (the parent). This value was corrected for the probability that events occur in one of these hotspot regions by chance via simulation.
The accuracy with which is measured increases with the number of crossovers observed for that parent, hence parents with more observed crossovers should be given higher weighting (large nuclear families are advantageous in this situation). We weighted individuals by creating pseudo-counts of hotspot events where is the number of crossover events observed for parent . We then fit a standard Binomial Generalised Linear Model (GLM) with as the response and the genetic dosage at each SNP as the covariate. We then performed a likelihood ratio test between this model of association and the ‘null’ model where no genetic variant is included. Variants were imputed from the 1000 Genomes March 2012 reference panel and filtered such that all variants had and in all cohorts.
The use of the Binomial GLM allows us to leverage parents who are part of typically uninformative meioses, where it is unlikely the majority of crossover events were detected. Such individuals are simply down weighted in our association testing.
The accuracy with which is measured increases with the number of crossovers observed for that parent, hence parents with more observed crossovers should be given higher weighting (large nuclear families are advantageous in this situation). We weighted individuals by creating pseudo-counts of hotspot events where is the number of crossover events observed for parent . We then fit a standard Binomial Generalised Linear Model (GLM) with as the response and the genetic dosage at each SNP as the covariate. We then performed a likelihood ratio test between this model of association and the ‘null’ model where no genetic variant is included. Variants were imputed from the 1000 Genomes March 2012 reference panel and filtered such that all variants had and in all cohorts.
The use of the Binomial GLM allows us to leverage parents who are part of typically uninformative meioses, where it is unlikely the majority of crossover events were detected. Such individuals are simply down weighted in our association testing.
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