Description Usage Arguments Details Author(s) Examples
This function takes as input a fitted model object, typically created by the standard R functions lm, glm or coxph, and fitted to individual-level genotype and phenotype data. The model is augmented by adding a term for each single SNP in turn and the refitted. This provides the single SNP summary association statistics needed to apply the summry statistic methods.
1 | grs.onesnp.apply(params, object, coeff.extract.fun = coeff.extract)
|
params |
a data frame, see |
object |
a fitted model object of class lm, glm, or coxph |
coeff.extract.fun |
function that extracts Estimate and Std.Err
from fitted model objects, see |
By default this uses coeff.extract
to detect the class of object and handles
coefficient extraction appropriately. Supply your own function if you
have an object that works with update (supply your own update too).
Toby Johnson Toby.x.Johnson@gsk.com
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | library(survival)
data(t2d.scores)
data(t2dex)
mycoxph <- coxph(Surv(FollowupDays,FollowupT2D) ~ Overweight,
data = t2dex$data) # fit null model
assoc1 <- grs.onesnp.apply(t2d.scores, mycoxph) # single SNP association
## risk score fit from single SNPs
unlist(grs.summary(t2d.scores$coef, assoc1$beta, assoc1$se,
n = length(residuals(mycoxph))))
## compare direct analysis of subject-specific data
t2dex <- grs.make.scores(t2d.scores, t2dex)
coxph(Surv(FollowupDays,FollowupT2D) ~ Overweight + T2D2010.score,
data = t2dex$data)
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