Filtering Variants for LD Score Regression

The majority of the sets of summary statistics that we analyzed did not contain information about sample minor allele frequency or imputation quality. In order to restrict to a set of common, well-imputed variants, we retained only those SNPs in the HapMap 3 reference panel^{41 (link)} for the LD Score regression. To guard against underestimation of LD Score from summing only LD with variants within a 1cM window, we removed variants in regions with exceptionally long-range LD^{42 (link)} from the LD Score regression (NB LD with these variants were included in the estimation of LD Score). Lastly, we excluded pericentromeric regions (defined as ± 3 cM from a centromere) from the LD Score regression, because these regions are enriched for sequence gaps, which may lead to underestimation of LD Score, and depleted for genes, which may reduce the probability of association to phenotype^{43 (link),44 (link)}. The final set of variants retained for LD Score regression on real data consisted of approximately 1.1 million variants.

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Bulik-Sullivan B.K., Loh P.R., Finucane H., Ripke S., Yang J., Patterson N., Daly M.J., Price A.L, & Neale B.M. (2015). LD Score Regression Distinguishes Confounding from Polygenicity in Genome-Wide Association Studies. Nature genetics, 47(3), 291-295.

Publication 2015

Centromere Genes Hapmap Snps

Corresponding Organization :

Other organizations : Broad Institute, Harvard University, Massachusetts General Hospital, University of Queensland

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Variable analysis

independent variables

Restricting to a set of common, well-imputed variants by retaining only those SNPs in the HapMap 3 reference panel
Removing variants in regions with exceptionally long-range LD from the LD Score regression
Excluding pericentromeric regions (defined as ± 3 cM from a centromere) from the LD Score regression

dependent variables

Not explicitly mentioned

control variables

LD with the removed variants were included in the estimation of LD Score
Pericentromeric regions are enriched for sequence gaps, which may lead to underestimation of LD Score, and depleted for genes, which may reduce the probability of association to phenotype

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