## ----setup, include = FALSE---------------------------------------------------
LOCAL <- identical(Sys.getenv("LOCAL"), "TRUE")
#LOCAL=FALSE
knitr::opts_chunk$set(purl = LOCAL)
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.width=5
)
## ---- eval = FALSE------------------------------------------------------------
# devtools::install_github("mariechion/mi4p")
## -----------------------------------------------------------------------------
library(mi4p)
## -----------------------------------------------------------------------------
set.seed(4619)
datasim <- protdatasim()
str(datasim)
## -----------------------------------------------------------------------------
attr(datasim, "metadata")
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
MV1pct.NA.data <- MVgen(dataset = datasim[,-1], prop_NA = 0.01)
MV1pct.NA.data
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
MV1pct.impMLE <- multi.impute(data = MV1pct.NA.data, conditions = attr(datasim,"metadata")$Condition, method = "MLE", parallel = FALSE)
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
print(paste(Sys.time(), "Dataset", 1, "out of", 1))
MV1pct.impMLE.VarRubin.Mat <- rubin2.all(data = MV1pct.impMLE, metacond = attr(datasim, "metadata")$Condition)
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
print(paste("Dataset", 1, "out of",1, Sys.time()))
MV1pct.impMLE.VarRubin.S2 <- as.numeric(lapply(MV1pct.impMLE.VarRubin.Mat, function(aaa){
DesMat = mi4p::make.design(attr(datasim, "metadata"))
return(max(diag(aaa)%*%t(DesMat)%*%DesMat))
}))
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
MV1pct.impMLE.mi4limma.res <- mi4limma(qData = apply(MV1pct.impMLE,1:2,mean),
sTab = attr(datasim, "metadata"),
VarRubin = sqrt(MV1pct.impMLE.VarRubin.S2))
MV1pct.impMLE.mi4limma.res
(simplify2array(MV1pct.impMLE.mi4limma.res)$P_Value.A_vs_B_pval)[1:10]
(simplify2array(MV1pct.impMLE.mi4limma.res)$P_Value.A_vs_B_pval)[11:200]<=0.05
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
sum((simplify2array(MV1pct.impMLE.mi4limma.res)$P_Value.A_vs_B_pval)[1:10]<=0.05)/10
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
sum((simplify2array(MV1pct.impMLE.mi4limma.res)$P_Value.A_vs_B_pval)[11:200]<=0.05)/190
## ---- cache=TRUE, eval=LOCAL--------------------------------------------------
MV1pct.impMLE.dapar.res <-limmaCompleteTest.mod(qData = apply(MV1pct.impMLE,1:2,mean), sTab = attr(datasim, "metadata"))
MV1pct.impMLE.dapar.res
## -----------------------------------------------------------------------------
set.seed(4619)
norm.200.m100.sd1.vs.m200.sd1.list <- lapply(1:100, protdatasim)
metadata <- attr(norm.200.m100.sd1.vs.m200.sd1.list[[1]],"metadata")
## ---- eval=FALSE--------------------------------------------------------------
# library(foreach)
# doParallel::registerDoParallel(cores=NULL)
# requireNamespace("foreach",quietly = TRUE)
## ---- eval=FALSE--------------------------------------------------------------
# MV1pct.NA.data <- foreach::foreach(iforeach = norm.200.m100.sd1.vs.m200.sd1.list,
# .errorhandling = 'stop', .verbose = T) %dopar%
# MVgen(dataset = iforeach[,-1], prop_NA = 0.01)
## ---- eval=FALSE--------------------------------------------------------------
# MV1pct.impMLE <- foreach::foreach(iforeach = MV1pct.NA.data,
# .errorhandling = 'stop', .verbose = F) %dopar%
# multi.impute(data = iforeach, conditions = metadata$Condition,
# method = "MLE", parallel = F)
## ---- eval=FALSE--------------------------------------------------------------
# MV1pct.impMLE.VarRubin.Mat <- lapply(1:length(MV1pct.impMLE), function(index){
# print(paste(Sys.time(), "Dataset", index, "out of", length(MV1pct.impMLE)))
# rubin2.all(data = MV1pct.impMLE[[index]], metacond = metadata$Condition)
# })
## ---- eval=FALSE--------------------------------------------------------------
# MV1pct.impMLE.VarRubin.S2 <- lapply(1:length(MV1pct.impMLE.VarRubin.Mat), function(id.dataset){
# print(paste("Dataset", id.dataset, "out of",length(MV1pct.impMLE.VarRubin.Mat), Sys.time()))
# as.numeric(lapply(MV1pct.impMLE.VarRubin.Mat[[id.dataset]], function(aaa){
# DesMat = mi4p::make.design(metadata)
# return(max(diag(aaa)%*%t(DesMat)%*%DesMat))
# }))
# })
## ---- eval=FALSE--------------------------------------------------------------
# MV1pct.impMLE.mi4limma.res <- foreach(iforeach = 1:100, .errorhandling = 'stop', .verbose = T) %dopar%
# mi4limma(qData = apply(MV1pct.impMLE[[iforeach]],1:2,mean),
# sTab = metadata,
# VarRubin = sqrt(MV1pct.impMLE.VarRubin.S2[[iforeach]]))
#
# MV1pct.impMLE.dapar.res <- foreach(iforeach = 1:100, .errorhandling = 'stop', .verbose = T) %dopar%
# limmaCompleteTest.mod(qData = apply(MV1pct.impMLE[[iforeach]],1:2,mean),
# sTab = metadata)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.