Association

Association

Association can be performed using two approaches. One based on testing differences in allele frequencies between cases and control while the other is based on a generalized linear framework which allowes for including additional covariates. Both methods takes the uncertaincy of the genotypes into account.

Case control association using allele frequencies

To test for differences in the allele frequency genotype likelihood need to be provided or estimated. If alignment files are your input then -doLike must be invoked.

-doAsso [int]

1: The test is performed assuming the minor allele is known
3: The test is performed summing over all possible minor alleles

-yBin [file]

a file containing the case control status. 0 being the controls, 1 being the cases and -999 being missing phenotypes. The file should contain a single phenotype entry per line. Example of cases control phenotype file

cite kim et al.

Score statistic

To perform the test in a generalized linear framework posterior genotype probabilities must be provided or estimated. If alignment files are your input then -doLike, -doMaf, -doPost must be invoked. If input files are genotype likelihoods then -doMaf, -doPost must be invoked. Beagle output files can be used directly.

-doAsso [int]

2: The test is based on a score statistic from a generalized linear framework

-yBin [file]

a file containing the case control status. 0 being the controls, 1 being the cases and -999 being missing phenotypes. The file should contain a single phenotype entry per line. Example of cases control phenotype file

-yQuant [file]

a file containing the phenotype values.-999 being missing phenotypes. The file should contain a single phenotype entry per line. Example of a quantitative phenotype file

-cov [file]

a files containing additional covariates in the analysis. Each lines should contain the additional covariates for a single individuals. Thus the number of lines should match the number of individuals and the number of coloums should match the number of additional covariates. Example of a covariance file

-minHigh [int]

default = 10
This approach needs a certain amount of variability in the genotype probabilities. minHigh filters out sites that does not have at least [int] number of heterozygoes and homogoes genotype with at least 0.9 probability. This filter avoids the scenario where all individuals are heterozygoes with a high probability.

-minCount [int]

default = 10
The minimum expected minor alleles in the sample. This is the frequency multiplied by to times the number of individuals. Performing association on extremely low minor allele frequencies does not make sence.

cite skotte et al.