tests/testthat/test_GENESIS.R
In UW-GAC/genesis2_tests: genesis assocation testing code rewrite
context("compare to GENESIS")
test_that("fitNullMod matches fitNullReg - linear", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, verbose=FALSE)
df <- .asDataFrame(dat)
lm.genesis <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), verbose=FALSE)
expect_equivalent(nullmod$fixef, lm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lm.genesis$resid.response)
expect_equivalent(nullmod$logLik, lm.genesis$logLik)
expect_equivalent(nullmod$AIC, lm.genesis$AIC)
expect_equivalent(nullmod$workingY, lm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lm.genesis$sigma^2)
expect_equal(nullmod$family$family, lm.genesis$family$family)
})
test_that("fitNullMod matches fitNullReg - binary", {
dat <- .testNullInputs(binary=TRUE)
nullmod <- fitNullMod(dat$y, dat$X, family="binomial", verbose=FALSE)
df <- .asDataFrame(dat)
glm.genesis <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), family="binomial", verbose=FALSE)
expect_equivalent(nullmod$fixef, glm.genesis$fixef)
expect_equivalent(nullmod$betaCov, glm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, glm.genesis$resid.response)
expect_equivalent(nullmod$logLik, glm.genesis$logLik)
expect_equivalent(nullmod$AIC, glm.genesis$AIC)
expect_equivalent(nullmod$workingY, glm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, glm.genesis$model.matrix)
expect_equal(nullmod$family$family, glm.genesis$family$family)
expect_equivalent(nullmod$varComp, glm.genesis$sigma^2)
})
test_that("fitNullMod matches fitNullMM - linear, no group", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, verbose=FALSE)
df <- .asDataFrame(dat)
lmm.genesis <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR)
expect_equivalent(nullmod$AIC, lmm.genesis$AIC)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, lmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-9))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS)
})
test_that("fitNullMod matches fitNullMM - linear, with group", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, group.idx=dat$group.idx, verbose=FALSE)
df <- .asDataFrame(dat)
lmm.genesis <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, group.var="group", verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR)
expect_equivalent(nullmod$AIC, lmm.genesis$AIC)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, lmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-9))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS)
})
test_that("fitNullMod matches fitNullMM - binary", {
varCompZero <- TRUE
while(varCompZero){
dat <- .testNullInputs(binary=TRUE)
df <- .asDataFrame(dat)
glmm.genesis <- tryCatch({
GENESIS::fitNullMM(df, outcome="y", covars = c("X1", "X2", "X3"), covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
},
warning = function(w){return(list(message = "warning"))},
error = function(e){return(list(message = "error"))}
)
if (!is.null(glmm.genesis$message)) next
if (glmm.genesis$varComp[1] != 0 ) varCompZero <- FALSE
}
nullmod <- fitNullMod(dat$y, dat$X, covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
expect_equivalent(nullmod$fixef, glmm.genesis$fixef, tolerance=1e-6)
expect_equivalent(nullmod$betaCov, glmm.genesis$betaCov, tolerance=1e-6)
expect_equivalent(nullmod$resid.marginal, glmm.genesis$resid.marginal, tolerance=1e-6)
expect_equivalent(nullmod$logLik, glmm.genesis$logLik, tolerance=1e-6)
expect_equivalent(nullmod$logLikR, glmm.genesis$logLikR, tolerance=1e-6)
expect_equivalent(nullmod$AIC, glmm.genesis$AIC, tolerance=1e-6)
expect_equivalent(nullmod$workingY, glmm.genesis$workingY, tolerance=1e-6)
expect_equivalent(nullmod$model.matrix, glmm.genesis$model.matrix, tolerance=1e-6)
expect_equivalent(nullmod$varComp, glmm.genesis$varComp, tolerance=1e-6)
expect_equivalent(nullmod$varCompCov, glmm.genesis$varCompCov, tolerance=1e-4) ## not smaller then 1e-6 because values were not updated after convergence. However, this is not important, because the variance component values are converged at the desired level!
expect_equivalent(nullmod$family$family, glmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, glmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - glmm.genesis$cholSigmaInv) < 1e-6))
})
test_that("fitNullMod matches fitNullMM - no variance components", {
n <- 100
dat <- .testNullInputs(n)
df <- .asDataFrame(dat)
## I need to create a junk correlation matrix that will zero out as having variance component zero...
varCompJunk <- TRUE
while(varCompJunk){
cor.mat <- diag(rnorm(n, sd = 0.01))
dimnames(cor.mat) <- list(df$scanID, df$scanID)
lmm.genesis <- GENESIS::fitNullMM(df, "y", covars=c("X1", "X2", "X3"), covMatList=cor.mat, group.var="group", verbose=FALSE)
if (lmm.genesis$varComp[1] == 0 ) varCompJunk <- FALSE
}
nullmod <- fitNullMod(dat$y, dat$X, group.idx=dat$group.idx, verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef, tolerance=1e-6)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov, tolerance=1e-6)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal, tolerance=1e-6)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik, tolerance=1e-6)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR, tolerance=1e-6)
## currently GENESIS has a mistake, in AUC calculation it uses the number of
## matrices and groups used, but not the actual number of non-zero variance components.
## so this "2" fixes for it.
expect_equivalent(nullmod$AIC, lmm.genesis$AIC - 2, tolerance=1e-6)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY, tolerance=1e-6)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix, tolerance=1e-6)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp[2:3], tolerance=1e-6)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov[2:3, 2:3], tolerance=1e-4)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-6))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS, tolerance=1e-6)
})
test_that("nullModelTestPrep matches calculateProjection", {
n <- 100
dat <- .testNullInputs(n)
geno <- .testGenoMatrix(n)
df <- .asDataFrame(dat)
# basic
nullmod <- fitNullMod(dat$y, dat$X, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(nullmod$Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with covMatList
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with group
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, group.idx=dat$group.idx, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, group.var="group", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
})
test_that("nullModelTestPrep vs calculateProjection - binary", {
n <- 100
geno <- .testGenoMatrix(n)
## reps <- 0
## varCompZero <- TRUE
## while(varCompZero & reps < 10){
dat <- .testNullInputs(n, binary=TRUE)
df <- .asDataFrame(dat)
## glmm.genesis <- tryCatch({
## GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=cor.mat, family="binomial", verbose=FALSE, maxIter=10)
## },
## warning = function(w){return(list(message = "warning"))},
## error = function(e){return(list(message = "error"))}
## )
## if (!is.null(glmm.genesis$message)) next
## if (glmm.genesis$varComp[1] != 0 ) varCompZero <- FALSE
## reps <- reps + 1
## }
## if (varCompZero) stop("could not generate nonzero varComp")
# basic
nullmod <- fitNullMod(dat$y, dat$X, family="binomial", verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), family="binomial", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with covMatList
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, family="binomial", verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-7))
})
UW-GAC/genesis2_tests documentation built on May 9, 2019, 9:57 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
context("compare to GENESIS")
test_that("fitNullMod matches fitNullReg - linear", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, verbose=FALSE)
df <- .asDataFrame(dat)
lm.genesis <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), verbose=FALSE)
expect_equivalent(nullmod$fixef, lm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lm.genesis$resid.response)
expect_equivalent(nullmod$logLik, lm.genesis$logLik)
expect_equivalent(nullmod$AIC, lm.genesis$AIC)
expect_equivalent(nullmod$workingY, lm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lm.genesis$sigma^2)
expect_equal(nullmod$family$family, lm.genesis$family$family)
})
test_that("fitNullMod matches fitNullReg - binary", {
dat <- .testNullInputs(binary=TRUE)
nullmod <- fitNullMod(dat$y, dat$X, family="binomial", verbose=FALSE)
df <- .asDataFrame(dat)
glm.genesis <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), family="binomial", verbose=FALSE)
expect_equivalent(nullmod$fixef, glm.genesis$fixef)
expect_equivalent(nullmod$betaCov, glm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, glm.genesis$resid.response)
expect_equivalent(nullmod$logLik, glm.genesis$logLik)
expect_equivalent(nullmod$AIC, glm.genesis$AIC)
expect_equivalent(nullmod$workingY, glm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, glm.genesis$model.matrix)
expect_equal(nullmod$family$family, glm.genesis$family$family)
expect_equivalent(nullmod$varComp, glm.genesis$sigma^2)
})
test_that("fitNullMod matches fitNullMM - linear, no group", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, verbose=FALSE)
df <- .asDataFrame(dat)
lmm.genesis <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR)
expect_equivalent(nullmod$AIC, lmm.genesis$AIC)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, lmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-9))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS)
})
test_that("fitNullMod matches fitNullMM - linear, with group", {
dat <- .testNullInputs()
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, group.idx=dat$group.idx, verbose=FALSE)
df <- .asDataFrame(dat)
lmm.genesis <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, group.var="group", verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR)
expect_equivalent(nullmod$AIC, lmm.genesis$AIC)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, lmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-9))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS)
})
test_that("fitNullMod matches fitNullMM - binary", {
varCompZero <- TRUE
while(varCompZero){
dat <- .testNullInputs(binary=TRUE)
df <- .asDataFrame(dat)
glmm.genesis <- tryCatch({
GENESIS::fitNullMM(df, outcome="y", covars = c("X1", "X2", "X3"), covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
},
warning = function(w){return(list(message = "warning"))},
error = function(e){return(list(message = "error"))}
)
if (!is.null(glmm.genesis$message)) next
if (glmm.genesis$varComp[1] != 0 ) varCompZero <- FALSE
}
nullmod <- fitNullMod(dat$y, dat$X, covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
expect_equivalent(nullmod$fixef, glmm.genesis$fixef, tolerance=1e-6)
expect_equivalent(nullmod$betaCov, glmm.genesis$betaCov, tolerance=1e-6)
expect_equivalent(nullmod$resid.marginal, glmm.genesis$resid.marginal, tolerance=1e-6)
expect_equivalent(nullmod$logLik, glmm.genesis$logLik, tolerance=1e-6)
expect_equivalent(nullmod$logLikR, glmm.genesis$logLikR, tolerance=1e-6)
expect_equivalent(nullmod$AIC, glmm.genesis$AIC, tolerance=1e-6)
expect_equivalent(nullmod$workingY, glmm.genesis$workingY, tolerance=1e-6)
expect_equivalent(nullmod$model.matrix, glmm.genesis$model.matrix, tolerance=1e-6)
expect_equivalent(nullmod$varComp, glmm.genesis$varComp, tolerance=1e-6)
expect_equivalent(nullmod$varCompCov, glmm.genesis$varCompCov, tolerance=1e-4) ## not smaller then 1e-6 because values were not updated after convergence. However, this is not important, because the variance component values are converged at the desired level!
expect_equivalent(nullmod$family$family, glmm.genesis$family$family)
expect_equivalent(nullmod$zeroFLAG, glmm.genesis$zeroFLAG)
expect_true(all(abs(nullmod$cholSigmaInv - glmm.genesis$cholSigmaInv) < 1e-6))
})
test_that("fitNullMod matches fitNullMM - no variance components", {
n <- 100
dat <- .testNullInputs(n)
df <- .asDataFrame(dat)
## I need to create a junk correlation matrix that will zero out as having variance component zero...
varCompJunk <- TRUE
while(varCompJunk){
cor.mat <- diag(rnorm(n, sd = 0.01))
dimnames(cor.mat) <- list(df$scanID, df$scanID)
lmm.genesis <- GENESIS::fitNullMM(df, "y", covars=c("X1", "X2", "X3"), covMatList=cor.mat, group.var="group", verbose=FALSE)
if (lmm.genesis$varComp[1] == 0 ) varCompJunk <- FALSE
}
nullmod <- fitNullMod(dat$y, dat$X, group.idx=dat$group.idx, verbose=FALSE)
expect_equivalent(nullmod$fixef, lmm.genesis$fixef, tolerance=1e-6)
expect_equivalent(nullmod$betaCov, lmm.genesis$betaCov, tolerance=1e-6)
expect_equivalent(nullmod$resid.marginal, lmm.genesis$resid.marginal, tolerance=1e-6)
expect_equivalent(nullmod$logLik, lmm.genesis$logLik, tolerance=1e-6)
expect_equivalent(nullmod$logLikR, lmm.genesis$logLikR, tolerance=1e-6)
## currently GENESIS has a mistake, in AUC calculation it uses the number of
## matrices and groups used, but not the actual number of non-zero variance components.
## so this "2" fixes for it.
expect_equivalent(nullmod$AIC, lmm.genesis$AIC - 2, tolerance=1e-6)
expect_equivalent(nullmod$workingY, lmm.genesis$workingY, tolerance=1e-6)
expect_equivalent(nullmod$model.matrix, lmm.genesis$model.matrix, tolerance=1e-6)
expect_equivalent(nullmod$varComp, lmm.genesis$varComp[2:3], tolerance=1e-6)
expect_equivalent(nullmod$varCompCov, lmm.genesis$varCompCov[2:3, 2:3], tolerance=1e-4)
expect_equivalent(nullmod$family$family, lmm.genesis$family$family)
expect_true(all(abs(nullmod$cholSigmaInv - lmm.genesis$cholSigmaInv) < 1e-6))
expect_equivalent(nullmod$RSS, lmm.genesis$RSS, tolerance=1e-6)
})
test_that("nullModelTestPrep matches calculateProjection", {
n <- 100
dat <- .testNullInputs(n)
geno <- .testGenoMatrix(n)
df <- .asDataFrame(dat)
# basic
nullmod <- fitNullMod(dat$y, dat$X, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(nullmod$Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with covMatList
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with group
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, group.idx=dat$group.idx, verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, group.var="group", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
})
test_that("nullModelTestPrep vs calculateProjection - binary", {
n <- 100
geno <- .testGenoMatrix(n)
## reps <- 0
## varCompZero <- TRUE
## while(varCompZero & reps < 10){
dat <- .testNullInputs(n, binary=TRUE)
df <- .asDataFrame(dat)
## glmm.genesis <- tryCatch({
## GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=cor.mat, family="binomial", verbose=FALSE, maxIter=10)
## },
## warning = function(w){return(list(message = "warning"))},
## error = function(e){return(list(message = "error"))}
## )
## if (!is.null(glmm.genesis$message)) next
## if (glmm.genesis$varComp[1] != 0 ) varCompZero <- FALSE
## reps <- reps + 1
## }
## if (varCompZero) stop("could not generate nonzero varComp")
# basic
nullmod <- fitNullMod(dat$y, dat$X, family="binomial", verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullReg(df, outcome="y", covars=c("X1", "X2", "X3"), family="binomial", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-9))
# with covMatList
nullmod <- fitNullMod(dat$y, dat$X, dat$cor.mat, family="binomial", verbose=FALSE)
Xtilde <- calcXtilde(nullmod, geno)
nullmod.orig <- GENESIS::fitNullMM(df, outcome="y", covars=c("X1", "X2", "X3"), covMatList=dat$cor.mat, family="binomial", verbose=FALSE)
proj <- GENESIS:::.calculateProjection(nullmod.orig, test="", burden.test="")
expect_true(all(abs(Xtilde - crossprod(proj$Mt, geno)) < 1e-9))
expect_true(all(abs(nullmod$resid - proj$resid) < 1e-7))
})
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.