R/Allstats.R
In CHKim5/LMSstat: AUTOMATION OF STATISTICAL TESTS WITH AN IDENTICAL DATA INPUT.
#' Automatically processes T-test, U-test, Anova, Scheffe(Anova Post-Hoc), Krukal Wallis, Dunn-test(BH adjusted,(Kurkal Wallis Post-Hoc)) while allowing adjustment of FDR
#'
#' @param Data csv file with Header as False First column with Sample Second column with Multilevel(Mixomics) so that it can be compatible with other multivariate statistics Third column with Group information. Rest of the columns are the metabolites to be tested.
#' @param Adjust_p_value Set True if FDR adjustments are to be made. If not set False
#' @param Adjust_method adjustment methods frequently used. "holm", "hochberg", "hommel", "bonferroni", "BH", "BY","fdr", "none"
#'
#' @return List including Result Matrix of p-values, converted datas.
#' @export
#'
#' @examples data(Data)
#' Result<-Allstats(Data)
#' Result<-Allstats_new(Data) # faster version contributed by Daehwan Kim
#'
#'
Allstats<-function (Data, Adjust_p_value = T, Adjust_method = "BH")
{
LETTERS210729 <- apply(as.matrix(1:400000),1, function(x) paste0("V",x))
colnames(Data) <- Data[1, ]
Data <- Data[-1, -2]
Data<-Data %>% dplyr::arrange(Group)
Data_renamed <- Data
nmet <- ncol(Data) - 2
colnames(Data_renamed) <- c(colnames(Data[1:2]), LETTERS210729[1:nmet])
rownames(Data_renamed) <- Data[, 1]
Data_renamed_raw <- Data_renamed[, -c(1, 2)]
Data_renamed_raw <- apply(Data_renamed_raw, 2, as.numeric)
Data_final <- cbind(Data[, 1:2], Data_renamed_raw)
if (length(unique(Data_final$Group)) == 2) {
suppressWarnings({
for (Gnum in 1:length(unique(Data$Group))) {
assign(paste("Data", unique(Data$Group)[Gnum],
sep = "_"), dplyr::filter(Data_final, Group ==
unique(Data_final$Group)[Gnum]))
}
Result <- matrix(data = NA, nrow = (ncol(Data_final) -
2), ncol = (2 * choose(length(unique(Data$Group)),
2)))
Rounder <- 1
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
t.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"T_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"T_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("T-test has finished")
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
wilcox.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"U_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"U_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("U-test has finished")
Names <- NULL
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
Names <- rbind(Names, paste(unique(Data$Group)[C],
unique(Data$Group)[H], sep = "-"))
}
}
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1]
Result_U <- Result[, 2]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
})
}
else if (length(unique(Data_final$Group)) > 2) {
suppressWarnings({
for (Gnum in 1:length(unique(Data$Group))) {
assign(paste("Data", unique(Data$Group)[Gnum],
sep = "_"), filter(Data_final, Group ==
unique(Data_final$Group)[Gnum]))
}
Result <- matrix(data = NA, nrow = (ncol(Data_final) -
2), ncol = (2 + 4 * choose(length(unique(Data$Group)),
2)))
Rounder <- 1
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
t.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"T_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"T_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("T-test has finished")
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
wilcox.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"U_test", sep = "_"),Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"U_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("U-test has finished")
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
Ano_In <- aov(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final)
summary(Ano_In)[[1]][["Pr(>F)"]][1] },
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
"Anova", sep = "_"), Out)
}
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Anova", sep = "_")))
}
Rounder <- Rounder + 1
}
else {
print("Anova went wrong")
}
for (met in 1:(ncol(Data) - 2)) {
assign(paste(LETTERS210729[met], "Anova_Post_Hoc",
sep = "_"), DescTools::PostHocTest(aov(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final), method = "scheffe"))
}
for (Ano_numb in 1:nrow(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])) {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Anova_Post_Hoc", sep = "_")))[["Group"]][Ano_numb,
4]
}
Rounder <- Rounder + 1
}
else {
print("Anova went wrong")
}
}
print("Anova & PostHoc has finished")
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
Kru_In <- kruskal.test(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final)
Kru_In[["p.value"]]},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
"Kruskal_Wallis", sep = "_"), Out)
}
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Kruskal_Wallis", sep = "_")))
}
Rounder <- Rounder + 1
}
else {
print("Kruskal went wrong")
}
for (met in 1:(ncol(Data) - 2)) {
assign(paste(LETTERS210729[met], "Dunn_Post_Hoc",
sep = "_"), FSA::dunnTest(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final, method = "bh"))
}
for (Kru_numb in 1:length(eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])) {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["P.adj"]][Kru_numb]
}
Rounder <- Rounder + 1
}
else {
print("Dunn went wrong")
}
}
print("Kruskal Wallis & PostHoc has finished")
Names <- NULL
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
Names <- rbind(Names, paste(unique(Data$Group)[C],
unique(Data$Group)[H], sep = "-"))
}
}
}
AN_Post_names <- NULL
for (nrow in 1:nrow(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])) {
AN_Post_names <- rbind(AN_Post_names, rownames(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])[nrow])
}
DU_post_names <- NULL
for (nrow in 1:length(eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])) {
DU_post_names <- rbind(DU_post_names, (eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])[nrow])
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"), "Anova", paste(AN_Post_names,
"ANO_posthoc", sep = "___"), "Kruskal_Wallis",
paste(DU_post_names, "Kru_posthoc(Dunn)",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
})
Result_T <- Result[, 1:choose(length(unique(Data$Group)),
2)]
Result_U <- Result[, (choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2))]
Result_Ano <- as.data.frame(Result[, (2 * choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2) +
1)])
colnames(Result_Ano) <- colnames(Result)[(2 * choose(length(unique(Data$Group)),
2) + 1)]
Result_Ano_P <- Result[, (2 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
1)]
Result_Kru <- as.data.frame(Result[, (3 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
2)])
colnames(Result_Kru) <- colnames(Result)[(3 * choose(length(unique(Data$Group)),
2) + 2)]
Result_Kru_P <- Result[, (3 * choose(length(unique(Data$Group)),
2) + 3):(4 * choose(length(unique(Data$Group)), 2) +
2)]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$Anova <- Result_Ano
Final$Anova_PostHoc <- Result_Ano_P
Final$KW <- Result_Kru
Final$Dunn <- Result_Kru_P
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
}
Allstats_new<-function (Data, Adjust_p_value = T, Adjust_method = "BH")
{
LETTERS210729 <- apply(as.matrix(1:400000),1, function(x) paste0("V",x))
colnames(Data) <- Data[1, ]
Data <- Data[-1, -2]
Data<-Data %>% dplyr::arrange(Group)
Data_renamed <- Data
nmet <- ncol(Data) - 2
colnames(Data_renamed) <- c(colnames(Data[1:2]), LETTERS210729[1:nmet])
rownames(Data_renamed) <- Data[, 1]
Data_renamed_raw <- Data_renamed[, -c(1, 2)]
Data_renamed_raw <- apply(Data_renamed_raw, 2, as.numeric)
Data_final <- cbind(Data[, 1:2], Data_renamed_raw)
Data_tmp <- data.table::as.data.table(Data_final)
if (length(unique(Data_final$Group)) == 2) {
groups_split <- split(Data_tmp, Data_tmp$Group)
####ttest####
split_t_test <- function(x, i) t.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_ttest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_t_test, i = i)))
df_ttest <- data.table::rbindlist(res_ttest)
Result <- df_ttest
print("T-test has finished")
####utest####
split_u_test <- function(x, i) wilcox.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_utest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_u_test, i = i)))
df_utest <- data.table::rbindlist(res_utest)
Result <- cbind(Result, df_utest)
print("U-test has finished")
###finalization####
Result <- as.matrix(Result)
Names <- NULL
for(i in 1:choose(length(groups_split),2)){
Names <- rbind(Names, paste(combn(names(groups_split), 2)[1,i],
combn(names(groups_split), 2)[2,i], sep = "-"))
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names, "t-test",
sep = "___"), paste(Names, "u-test",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1]
Result_U <- Result[, 2]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
else if (length(unique(Data_final$Group)) > 2) {
groups_split <- split(Data_tmp, Data_tmp$Group)
####ttest####
split_t_test <- function(x, i) t.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_ttest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_t_test, i = i)))
df_ttest <- data.table::rbindlist(res_ttest)
Result <- df_ttest
print("T-test has finished")
####utest####
split_u_test <- function(x, i) wilcox.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_utest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_u_test, i = i)))
df_utest <- data.table::rbindlist(res_utest)
Result <- cbind(Result, df_utest)
print("U-test has finished")
####ANOVA&PostHoc####
formula_anova <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_anova <- lapply(formula_anova, function(x) summary(aov(x, data = Data_tmp)))
names(res_anova) <- format(formula_anova)
p_anova <- unlist(lapply(res_anova, function(x) x[[1]]$"Pr(>F)"[1]))
df_anova <- data.table::data.table(p_anova)
Result <- cbind(Result, df_anova)
anovapost_name <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_anovapost <- lapply(anovapost_name, function(x) DescTools::PostHocTest(aov(x, data = Data_tmp), method = "scheffe"))
names(res_anovapost) <- format(anovapost_name)
post_anova <- lapply(res_anovapost, function(x) x[["Group"]][,4])
df_anova_post <- data.frame(post_anova)
Result <- cbind(Result, t(df_anova_post))
print("Anova & PostHoc has finished")
####KruskalWallis&PostHoc####
formula_kw <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_kw <- lapply(formula_anova, function(x) kruskal.test(x, data = Data_tmp)[["p.value"]])
names(res_kw) <- format(formula_kw)
p_kw <- unlist(res_kw)
df_kw <- data.table::data.table(p_kw)
Result <- cbind(Result, df_kw)
kwpost_name <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_kwpost <- lapply(kwpost_name, function(x) FSA::dunnTest(x, data = Data_tmp, method = "bh"))
names(res_kwpost) <- format(kwpost_name)
post_kw <- lapply(res_kwpost, function(x) x[["res"]][["P.adj"]])
df_kw_post <- t(data.table::data.table(data.frame(post_kw)))
Result <- cbind(Result, df_kw_post)
print("Kruskal Wallis & PostHoc has finished")
####finalization####
Result <- as.matrix(Result)
Names <- NULL
for(i in 1:choose(length(groups_split),2)){
Names <- rbind(Names, paste(combn(names(groups_split), 2)[1,i],
combn(names(groups_split), 2)[2,i], sep = "-"))
}
AN_Post_names <- rownames(df_anova_post)
DU_post_names <- res_kwpost[[1]]$res$Comparison
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"), "Anova", paste(AN_Post_names,
"ANO_posthoc", sep = "___"), "Kruskal_Wallis",
paste(DU_post_names, "Kru_posthoc(Dunn)",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1:choose(length(unique(Data$Group)),
2)]
Result_U <- Result[, (choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2))]
Result_Ano <- as.data.frame(Result[, (2 * choose(length(unique(Data$Group)),2) + 1):(2 * choose(length(unique(Data$Group)), 2) + 1)])
colnames(Result_Ano) <- colnames(Result)[(2 * choose(length(unique(Data$Group)),
2) + 1)]
Result_Ano_P <- Result[, (2 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
1)]
Result_Kru <- as.data.frame(Result[, (3 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
2)])
colnames(Result_Kru) <- colnames(Result)[(3 * choose(length(unique(Data$Group)),
2) + 2)]
Result_Kru_P <- Result[, (3 * choose(length(unique(Data$Group)),
2) + 3):(4 * choose(length(unique(Data$Group)), 2) +
2)]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$Anova <- Result_Ano
Final$Anova_PostHoc <- Result_Ano_P
Final$KW <- Result_Kru
Final$Dunn <- Result_Kru_P
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
}
CHKim5/LMSstat documentation built on Dec. 17, 2021, 12:55 p.m.
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#' Automatically processes T-test, U-test, Anova, Scheffe(Anova Post-Hoc), Krukal Wallis, Dunn-test(BH adjusted,(Kurkal Wallis Post-Hoc)) while allowing adjustment of FDR
#'
#' @param Data csv file with Header as False First column with Sample Second column with Multilevel(Mixomics) so that it can be compatible with other multivariate statistics Third column with Group information. Rest of the columns are the metabolites to be tested.
#' @param Adjust_p_value Set True if FDR adjustments are to be made. If not set False
#' @param Adjust_method adjustment methods frequently used. "holm", "hochberg", "hommel", "bonferroni", "BH", "BY","fdr", "none"
#'
#' @return List including Result Matrix of p-values, converted datas.
#' @export
#'
#' @examples data(Data)
#' Result<-Allstats(Data)
#' Result<-Allstats_new(Data) # faster version contributed by Daehwan Kim
#'
#'
Allstats<-function (Data, Adjust_p_value = T, Adjust_method = "BH")
{
LETTERS210729 <- apply(as.matrix(1:400000),1, function(x) paste0("V",x))
colnames(Data) <- Data[1, ]
Data <- Data[-1, -2]
Data<-Data %>% dplyr::arrange(Group)
Data_renamed <- Data
nmet <- ncol(Data) - 2
colnames(Data_renamed) <- c(colnames(Data[1:2]), LETTERS210729[1:nmet])
rownames(Data_renamed) <- Data[, 1]
Data_renamed_raw <- Data_renamed[, -c(1, 2)]
Data_renamed_raw <- apply(Data_renamed_raw, 2, as.numeric)
Data_final <- cbind(Data[, 1:2], Data_renamed_raw)
if (length(unique(Data_final$Group)) == 2) {
suppressWarnings({
for (Gnum in 1:length(unique(Data$Group))) {
assign(paste("Data", unique(Data$Group)[Gnum],
sep = "_"), dplyr::filter(Data_final, Group ==
unique(Data_final$Group)[Gnum]))
}
Result <- matrix(data = NA, nrow = (ncol(Data_final) -
2), ncol = (2 * choose(length(unique(Data$Group)),
2)))
Rounder <- 1
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
t.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"T_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"T_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("T-test has finished")
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
wilcox.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"U_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"U_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("U-test has finished")
Names <- NULL
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
Names <- rbind(Names, paste(unique(Data$Group)[C],
unique(Data$Group)[H], sep = "-"))
}
}
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1]
Result_U <- Result[, 2]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
})
}
else if (length(unique(Data_final$Group)) > 2) {
suppressWarnings({
for (Gnum in 1:length(unique(Data$Group))) {
assign(paste("Data", unique(Data$Group)[Gnum],
sep = "_"), filter(Data_final, Group ==
unique(Data_final$Group)[Gnum]))
}
Result <- matrix(data = NA, nrow = (ncol(Data_final) -
2), ncol = (2 + 4 * choose(length(unique(Data$Group)),
2)))
Rounder <- 1
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
t.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"T_test", sep = "_"), Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"T_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("T-test has finished")
for (Gnum_1 in 1:length(unique(Data$Group))) {
for (Gnum_2 in 1:length(unique(Data$Group))) {
if (Gnum_2 <= Gnum_1) {
next
}
else {
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
wilcox.test(x = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_1], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]),
y = (eval(parse(text = paste("Data",
unique(Data$Group)[Gnum_2], sep = "_")))[,
eval(parse(text = "LETTERS210729[met]"))]))[["p.value"]]
},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
unique(Data$Group)[Gnum_1], unique(Data$Group)[Gnum_2],
"U_test", sep = "_"),Out)
}
}
}
}
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
unique(Data$Group)[C], unique(Data$Group)[H],
"U_test", sep = "_")))
}
Rounder <- Rounder + 1
}
}
}
}
print("U-test has finished")
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
Ano_In <- aov(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final)
summary(Ano_In)[[1]][["Pr(>F)"]][1] },
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
"Anova", sep = "_"), Out)
}
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Anova", sep = "_")))
}
Rounder <- Rounder + 1
}
else {
print("Anova went wrong")
}
for (met in 1:(ncol(Data) - 2)) {
assign(paste(LETTERS210729[met], "Anova_Post_Hoc",
sep = "_"), DescTools::PostHocTest(aov(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final), method = "scheffe"))
}
for (Ano_numb in 1:nrow(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])) {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Anova_Post_Hoc", sep = "_")))[["Group"]][Ano_numb,
4]
}
Rounder <- Rounder + 1
}
else {
print("Anova went wrong")
}
}
print("Anova & PostHoc has finished")
for (met in 1:(ncol(Data) - 2)) {
Out<-tryCatch(
{
Kru_In <- kruskal.test(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final)
Kru_In[["p.value"]]},
error=function(cond) {
return(1)
}
)
assign(paste(as.character(LETTERS210729[met]),
"Kruskal_Wallis", sep = "_"), Out)
}
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Kruskal_Wallis", sep = "_")))
}
Rounder <- Rounder + 1
}
else {
print("Kruskal went wrong")
}
for (met in 1:(ncol(Data) - 2)) {
assign(paste(LETTERS210729[met], "Dunn_Post_Hoc",
sep = "_"), FSA::dunnTest(eval(parse(text = LETTERS210729[met])) ~
Group, data = Data_final, method = "bh"))
}
for (Kru_numb in 1:length(eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])) {
if (is.na(Result[1, Rounder]) == T) {
for (met_1 in 1:(ncol(Data_final) - 2)) {
Result[met_1, Rounder] <- eval(parse(text = paste(LETTERS210729[met_1],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["P.adj"]][Kru_numb]
}
Rounder <- Rounder + 1
}
else {
print("Dunn went wrong")
}
}
print("Kruskal Wallis & PostHoc has finished")
Names <- NULL
for (C in 1:length(unique(Data$Group))) {
for (H in 1:length(unique(Data$Group))) {
if (H <= C) {
next
}
else {
Names <- rbind(Names, paste(unique(Data$Group)[C],
unique(Data$Group)[H], sep = "-"))
}
}
}
AN_Post_names <- NULL
for (nrow in 1:nrow(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])) {
AN_Post_names <- rbind(AN_Post_names, rownames(eval(parse(text = paste(LETTERS210729[met],
"Anova_Post_Hoc", sep = "_")))[["Group"]])[nrow])
}
DU_post_names <- NULL
for (nrow in 1:length(eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])) {
DU_post_names <- rbind(DU_post_names, (eval(parse(text = paste(LETTERS210729[met],
"Dunn_Post_Hoc", sep = "_")))[["res"]][["Comparison"]])[nrow])
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"), "Anova", paste(AN_Post_names,
"ANO_posthoc", sep = "___"), "Kruskal_Wallis",
paste(DU_post_names, "Kru_posthoc(Dunn)",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
})
Result_T <- Result[, 1:choose(length(unique(Data$Group)),
2)]
Result_U <- Result[, (choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2))]
Result_Ano <- as.data.frame(Result[, (2 * choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2) +
1)])
colnames(Result_Ano) <- colnames(Result)[(2 * choose(length(unique(Data$Group)),
2) + 1)]
Result_Ano_P <- Result[, (2 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
1)]
Result_Kru <- as.data.frame(Result[, (3 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
2)])
colnames(Result_Kru) <- colnames(Result)[(3 * choose(length(unique(Data$Group)),
2) + 2)]
Result_Kru_P <- Result[, (3 * choose(length(unique(Data$Group)),
2) + 3):(4 * choose(length(unique(Data$Group)), 2) +
2)]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$Anova <- Result_Ano
Final$Anova_PostHoc <- Result_Ano_P
Final$KW <- Result_Kru
Final$Dunn <- Result_Kru_P
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
}
Allstats_new<-function (Data, Adjust_p_value = T, Adjust_method = "BH")
{
LETTERS210729 <- apply(as.matrix(1:400000),1, function(x) paste0("V",x))
colnames(Data) <- Data[1, ]
Data <- Data[-1, -2]
Data<-Data %>% dplyr::arrange(Group)
Data_renamed <- Data
nmet <- ncol(Data) - 2
colnames(Data_renamed) <- c(colnames(Data[1:2]), LETTERS210729[1:nmet])
rownames(Data_renamed) <- Data[, 1]
Data_renamed_raw <- Data_renamed[, -c(1, 2)]
Data_renamed_raw <- apply(Data_renamed_raw, 2, as.numeric)
Data_final <- cbind(Data[, 1:2], Data_renamed_raw)
Data_tmp <- data.table::as.data.table(Data_final)
if (length(unique(Data_final$Group)) == 2) {
groups_split <- split(Data_tmp, Data_tmp$Group)
####ttest####
split_t_test <- function(x, i) t.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_ttest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_t_test, i = i)))
df_ttest <- data.table::rbindlist(res_ttest)
Result <- df_ttest
print("T-test has finished")
####utest####
split_u_test <- function(x, i) wilcox.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_utest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_u_test, i = i)))
df_utest <- data.table::rbindlist(res_utest)
Result <- cbind(Result, df_utest)
print("U-test has finished")
###finalization####
Result <- as.matrix(Result)
Names <- NULL
for(i in 1:choose(length(groups_split),2)){
Names <- rbind(Names, paste(combn(names(groups_split), 2)[1,i],
combn(names(groups_split), 2)[2,i], sep = "-"))
}
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names, "t-test",
sep = "___"), paste(Names, "u-test",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1]
Result_U <- Result[, 2]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
else if (length(unique(Data_final$Group)) > 2) {
groups_split <- split(Data_tmp, Data_tmp$Group)
####ttest####
split_t_test <- function(x, i) t.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_ttest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_t_test, i = i)))
df_ttest <- data.table::rbindlist(res_ttest)
Result <- df_ttest
print("T-test has finished")
####utest####
split_u_test <- function(x, i) wilcox.test(groups_split[[x[1]]][[i]],
groups_split[[x[2]]][[i]])[["p.value"]]
res_utest <- lapply((seq_len(ncol(Data_tmp) - 2) + 2),
function(i) as.list(combn(names(groups_split), 2, split_u_test, i = i)))
df_utest <- data.table::rbindlist(res_utest)
Result <- cbind(Result, df_utest)
print("U-test has finished")
####ANOVA&PostHoc####
formula_anova <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_anova <- lapply(formula_anova, function(x) summary(aov(x, data = Data_tmp)))
names(res_anova) <- format(formula_anova)
p_anova <- unlist(lapply(res_anova, function(x) x[[1]]$"Pr(>F)"[1]))
df_anova <- data.table::data.table(p_anova)
Result <- cbind(Result, df_anova)
anovapost_name <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_anovapost <- lapply(anovapost_name, function(x) DescTools::PostHocTest(aov(x, data = Data_tmp), method = "scheffe"))
names(res_anovapost) <- format(anovapost_name)
post_anova <- lapply(res_anovapost, function(x) x[["Group"]][,4])
df_anova_post <- data.frame(post_anova)
Result <- cbind(Result, t(df_anova_post))
print("Anova & PostHoc has finished")
####KruskalWallis&PostHoc####
formula_kw <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_kw <- lapply(formula_anova, function(x) kruskal.test(x, data = Data_tmp)[["p.value"]])
names(res_kw) <- format(formula_kw)
p_kw <- unlist(res_kw)
df_kw <- data.table::data.table(p_kw)
Result <- cbind(Result, df_kw)
kwpost_name <- lapply(colnames(Data_tmp)[3:ncol(Data_tmp)], function(x) as.formula(paste0(x, " ~ Group")))
res_kwpost <- lapply(kwpost_name, function(x) FSA::dunnTest(x, data = Data_tmp, method = "bh"))
names(res_kwpost) <- format(kwpost_name)
post_kw <- lapply(res_kwpost, function(x) x[["res"]][["P.adj"]])
df_kw_post <- t(data.table::data.table(data.frame(post_kw)))
Result <- cbind(Result, df_kw_post)
print("Kruskal Wallis & PostHoc has finished")
####finalization####
Result <- as.matrix(Result)
Names <- NULL
for(i in 1:choose(length(groups_split),2)){
Names <- rbind(Names, paste(combn(names(groups_split), 2)[1,i],
combn(names(groups_split), 2)[2,i], sep = "-"))
}
AN_Post_names <- rownames(df_anova_post)
DU_post_names <- res_kwpost[[1]]$res$Comparison
rownames(Result) <- colnames(Data)[3:(ncol(Data_final))]
colnames(Result) <- c(paste(Names[, 1], "t-test",
sep = "___"), paste(Names[, 1], "u-test",
sep = "___"), "Anova", paste(AN_Post_names,
"ANO_posthoc", sep = "___"), "Kruskal_Wallis",
paste(DU_post_names, "Kru_posthoc(Dunn)",
sep = "___"))
if (Adjust_p_value == T) {
print("###########################################")
print(paste0("adjusted according to the ",
Adjust_method, " method"))
print("###########################################")
Result <- apply(Result, 2, function(x) {
p.adjust(x, method = Adjust_method)
})
}
else {
print("###########################################")
print("p_value not adjusted")
print("###########################################")
}
rm(list = setdiff(ls(), c("Data_renamed", "Data",
"Result", "LETTERS210729", "event",
"P_hoc", "Colors", "significant_variable_only")))
print("statistical test has finished")
Result_T <- Result[, 1:choose(length(unique(Data$Group)),
2)]
Result_U <- Result[, (choose(length(unique(Data$Group)),
2) + 1):(2 * choose(length(unique(Data$Group)), 2))]
Result_Ano <- as.data.frame(Result[, (2 * choose(length(unique(Data$Group)),2) + 1):(2 * choose(length(unique(Data$Group)), 2) + 1)])
colnames(Result_Ano) <- colnames(Result)[(2 * choose(length(unique(Data$Group)),
2) + 1)]
Result_Ano_P <- Result[, (2 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
1)]
Result_Kru <- as.data.frame(Result[, (3 * choose(length(unique(Data$Group)),
2) + 2):(3 * choose(length(unique(Data$Group)), 2) +
2)])
colnames(Result_Kru) <- colnames(Result)[(3 * choose(length(unique(Data$Group)),
2) + 2)]
Result_Kru_P <- Result[, (3 * choose(length(unique(Data$Group)),
2) + 3):(4 * choose(length(unique(Data$Group)), 2) +
2)]
print("subsets have been made")
Final <- list()
Final$Data <- Data
Final$Data_renamed <- Data_renamed
Final$Result <- Result
Final$Anova <- Result_Ano
Final$Anova_PostHoc <- Result_Ano_P
Final$KW <- Result_Kru
Final$Dunn <- Result_Kru_P
Final$t_test <- Result_T
Final$u_test <- Result_U
Final
}
}
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