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  • The following short R script provides the functions used to obtain the multi-marker Rasch genetic score for each subject of a dataset of interest, where ‘Geno’ is a data matrix of genoptypes coded by 0, 1 and 2, with subjects in rows and markers in columns: >library(eRM)>rasch.model = PCM(Geno)>score = person.parameter(rasch.model)$theta.table[, 1] If ‘Trait’ is a binary trait disease coded by 1 for cases and 0 for controls, the association of the multi-marker Rasch genetic score to the disease can then simply be assessed with a logistic model: >glm(Trait ∼ score, family = “binomial”) If ‘Trait’ is a quantitative trait, the association of the multi-marker Rasch genetic score to the disease can then simply be assessed with a linear model: >lm(Trait ∼ score) The performances of our Rasch-based multi-marker genetic association test are first evaluated in term of false-positive rate and power based on simulations over three scenarios of dependence between SNPs and varying levels of association.
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