Imputation without doing imputation: a new method for the detection of non-genotyped causal variants.
Bottom Line: This observation motivates popular but computationally intensive approaches based on imputation or haplotyping.These two SNPs are used as predictors in linear or logistic regression analysis to generate a final significance test.Previous analysis showed that fine-scale sequencing of a Gambian reference panel in the region of the known causal locus, followed by imputation, increased the signal of association to genome-wide significance levels.
Affiliation: Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom.Show MeSH
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Mentions: Figure 5 (top) shows a Manhattan plot of the P-values for chromosome 11 in the Gambian case/control dataset using single-SNP logistic regression implemented in PLINK. To adjust for population stratification, we first performed principal component analysis (PCA) using the smartpca routine of the EIGENSOFT package [Price et al., 2006] on 139,445 autosomal SNPs (pruned to be in low levels of LD with one another using the PLINK command “–indep 50 5 2”). The first three principal components from smartpca were then included as explanatory variables in the logistic regression models fitted by PLINK. (Note that Jallow et al.  also included the first three principal components to correct for population stratification, within a standard logistic regression framework). Colored in light gray in Figure 5 (top) are points that appear to be spurious associations and do not appear in the corresponding Manhattan plot shown in Jallow et al. ; we presume that these correspond to untrustworthy poorly-clustering SNPs that were removed “by eye.” A weak association signal ( at rs11036635) can be seen in the vicinity of the known causal SNP, rs334, whose position is shown as a dashed vertical line.
Affiliation: Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom.