Evaluate all variants for eQTL analysis

trajectory_finemapping.R

library(lme4)

set.seed(101)
 dd <- expand.grid(f1 = factor(1:10),
                   f2 = LETTERS[1:20], g=1:20, rep=1:15,
           KEEP.OUT.ATTRS=FALSE)
 summary(mu <- 5*(-4 + with(dd, as.integer(f1) + 4*as.numeric(f2))))
 dd$y <- rnbinom(nrow(dd), mu = mu, size = 0.5)
 str(dd)
 require("MASS")

# estimate parameters and theta
fit <- glmer.nb(y ~ f1*f2 + (1|g), data=dd)

# get theta from NB fit
theta.hat = lme4:::getNBdisp(fit))

# fit with fixed theta
fit2 = glmer(y ~ f1*f2 + (1|g), 
	data = dd, 
	family = negative.binomial(theta.hat))



fit1 = lm(y ~ SNP1)
fit2 = lm(y ~ SNP2)
cor(z1, z2) = cor(SNP1, SNP2)


fit1 = lm(y ~ SNP1 + time + SNP1:time)
fit2 = lm(y ~ SNP2 + time + SNP2:time)
cor(z1, z2) = f(SNP1, SNP2, time)