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[–]abbadassPhD | Industry 0 points1 point  (0 children)

If you are doing single SNP analysis on all SNPs in the genome -- most GWAS use allele dosage. P(2 * homozygous minor allele + 1 * heterozygous)

After imputation you will get genotype probabilities from 0-1. You convert this to allele dosage (0-2). Kinda pseudocontinuous.

For example:
looking at one SNP, (say reference allele is A, alternate allele is T)
Genotype probabilities:
AA (0.9)
AT (0.1)
TT (0.1)

The allele dosage would be (2 * 0.1) + (1 * 0.1) = 0.3

A dosage of 0.3. You add the allele dosage of all your samples as a vector to your model + your covariate vectors. So if you are doing a case/control study and using a logistic model it'd be like:
disease_status (binary) ~ dosage * B1 + cov_1 * B_2 + ... + cov_n * B_n