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: We used computer simulations to evaluate the performance of our proposed AI test and to compare it to other approaches. Figure 1 (left hand panels) shows a comparison of the powers to achieve various P-values in three different simulation scenarios for imputation, haplotype analysis, single-SNP logistic regression in PLINK, and the AI test (with the AI test taking different SNP window sizes, see Methods) respectively. Imputation was carried out using the program IMPUTE2 [Howie et al., 2009; Marchini et al., 2007] with prephasing [Howie et al., 2012] in SHAPEIT [Delaneau et al., 2012], using data from the 1000 Genomes Project [1000 Genomes Project Consortium et al., 2012] (Phase I interim data, updated release April 2012) as a reference panel. Haplotype analysis was carried out using the haplotype regression approach implemented in the program UNPHASED [Dudbridge, 2008; Dudbridge et al., 2011], using a sliding window of 5-SNP haplotypes.
Affiliation: Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne, United Kingdom.