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‎.Rbuildignore

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^.*\.Rproj$
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^\.Rproj\.user$

‎.gitignore

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.Rproj.user
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.Rhistory
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.RData
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.Ruserdata

‎DESCRIPTION

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Package: LMSstat
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Title: AUTOMATION OF STATISTICAL TESTS WITH AN IDENTICAL DATA INPUT.
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Version: 1.0.3
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Authors@R:
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person(given = "CHANG-HO",
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family = "KIM",
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role = c("aut", "cre"),
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email = "demizor3@gmail.com")
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Description: Automation of statistical tests with an identical data input.
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The package Includes most Statistical tests used in metabolomics,
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aiming to reduce arduous work searching for packages and changing data input.
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Encoding: UTF-8
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LazyData: true
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Roxygen: list(markdown = TRUE)
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RoxygenNote: 7.1.1
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License: MIT + file LICENSE
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biocViews:
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Imports:
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DescTools,
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FSA,
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viridis,
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gtools,
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ggplot2,
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scales,
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ggpubr,
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mixOmics,
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ecoflux,
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vegan,
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plyr,
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dplyr,
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tidyverse,
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pROC,
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ROCnReg
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Depends:
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tidyverse
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Remotes: jpshanno/ecoflux

‎LICENSE

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YEAR: 2021
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COPYRIGHT HOLDER: LMSALL authors

‎LICENSE.md

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# MIT License
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Copyright (c) 2021 LMSstat authors
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎LMSstat.Rproj

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Version: 1.0
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RestoreWorkspace: Default
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SaveWorkspace: Default
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AlwaysSaveHistory: Default
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EnableCodeIndexing: Yes
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UseSpacesForTab: Yes
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NumSpacesForTab: 2
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Encoding: UTF-8
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RnwWeave: Sweave
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LaTeX: pdfLaTeX
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AutoAppendNewline: Yes
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StripTrailingWhitespace: Yes
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BuildType: Package
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PackageUseDevtools: Yes
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PackageInstallArgs: --no-multiarch --with-keep.source

‎NAMESPACE

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exportPattern("^[[:alpha:]]+")

‎R/AS_barplot.R

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‎R/AS_boxplot.R

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#' Automatically save boxplots for all metabolites including asterisks for significance.
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#'
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#' @param data List inheriting from Allstats
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#' @param asterisk Choose asterisk to plot ("Dunn","Scheffe","u_test","t_test")
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#' @param significant_variable_only show significant variable only (T,F)
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#' @param color colors used for ggplots.
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#' @param legend_position legend position "none","left","right","bottom","top"
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#' @param order order of the groups; order = c("A","B","C")
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#' @param tip_length significance tip length
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#' @param label_size significance label size
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#' @param step_increase significance step increase
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#' @param width box width
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#' @param fig_width figure size
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#' @param fig_height figure size
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#'
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#' @return ggboxplot
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#' @export
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#'
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#' @examples D<-as.data.frame(cbind(LETTERS,rep(1,26),c(rep("A",7),rep("B",6),rep("C",13)),runif(26),runif(26)))
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#' Datas<-rbind(c("Sample","Multilevel","Group","some metabolite1","some metabolite2"),D)
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#' Test<-Allstats(Datas)
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#' AS_boxplot(Test,asterisk = "Dunn",significant_variable_only = F,color = c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099") )
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AS_boxplot<-function(data,
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asterisk="t_test",
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significant_variable_only=F,
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color=c("#FF3300","#FF6600","#FFCC00","#99CC00","#0066CC","#660099"),
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legend_position = "none",
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order = NULL,
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tip_length = 0.01,
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label_size = 2.88,
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step_increase = 0.05,
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width = 0.3,
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fig_width = NA,
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fig_height = NA){
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{#Summary
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###Plot_data_prep###
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ifelse(!dir.exists(file.path(getwd(), "barplot")), dir.create(file.path(getwd(), "boxplot")), FALSE)
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data[["Data_renamed"]]<-data[["Data_renamed"]] %>% plyr::mutate(
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ZZZZ =data[["Data_renamed"]][,2] )
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data[["Data_renamed"]]<-data[["Data_renamed"]][,c(-1,-2)]
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data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)]<-sapply(data[["Data_renamed"]][,1:(ncol(data[["Data_renamed"]])-1)],
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function(x) as.numeric(x))
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NAMES<-colnames(data[["Data"]][3:ncol(data[["Data"]])])
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data[["Data_renamed"]]$ZZZZ<-as.factor(data[["Data_renamed"]]$ZZZZ)
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colnames(data[["Data_renamed"]])[ncol(data[["Data_renamed"]])]<-"Group"
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Comb<-gtools::combinations(length(unique(data[["Data"]]$Group)),2,unique(data[["Data"]]$Group))
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ckey<-color[1:length(unique(data[["Data"]]$Group))]
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if (asterisk =="Scheffe"){
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p_val_data<-data[["Anova_PostHoc"]]}
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else if (asterisk =="t_test"){
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p_val_data<-data[["t_test"]]}
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else if (asterisk =="u_test"){
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p_val_data<-data[["u_test"]]}
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else if (asterisk =="Dunn"){
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p_val_data<-data[["Dunn"]]}
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else {
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print("Wrong asterisk input must be one of (Dunn,Scheffe,u_test,t_test)")}}
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###Plots###
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suppressWarnings(
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if (length(unique(data[["Data_renamed"]][["Group"]]))!=2) {
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for (number in 1:nrow(p_val_data)){
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if (number == round(nrow(p_val_data)/4)){print("25% complete")}
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if (number == round(nrow(p_val_data)/3)){print("33% complete")}
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if (number == round(nrow(p_val_data)/2)){print("50% complete")}
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if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
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if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
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if (number == nrow(p_val_data)){print("100% complete")}
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stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
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ncol = 2))
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stat.test[, 1:2] <- Comb
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if (asterisk == "Dunn"){
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rownames(stat.test)<-paste0(stat.test[,1]," - ",stat.test[,2])}
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else{
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rownames(stat.test)<-paste0(stat.test[,1],"-",stat.test[,2])}
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colnames(p_val_data)<-as.data.frame(strsplit(colnames(p_val_data),"___"))[1,]
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t1<-as.data.frame(t(as.data.frame(p_val_data)[number,]))
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t2<-stat.test
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t3<-merge(t2,t1,by=0)
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stat.test<-t3[,2:4]
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colnames(stat.test) <- c("group1", "group2",
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"p")
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stat.test<-stat.test %>% plyr::mutate(
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p.adj.signif = case_when(
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p > 0.05 ~ 'NS',
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p <= 0.05 &p > 0.01 ~ '*',
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p <= 0.01 ~ '**'
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)
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)
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stat.test<-stat.test[stat.test$p.adj.signif != "NS",]
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if (length(stat.test>4)){
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ggpubr::ggboxplot(data[["Data_renamed"]],
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x = "Group",
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y = colnames(data[["Data_renamed"]])[number],
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color = "Group",
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palette = ckey,
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add = "jitter",
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order = order,
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width = width)+
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scale_y_continuous(label=ecoflux::scientific_10x)+
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labs(title=NAMES[number],x =NULL, y = "Intensity")+
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theme_classic()+ ggplot2::theme(plot.title=element_text(size=15,
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face="bold",
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color="Black",
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hjust=0.5,
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lineheight=1.2), # title
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plot.subtitle=element_text(size=15,
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hjust=0.5), # subtitle
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plot.caption=element_text(size=15), # caption
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axis.title.x=element_text(vjust=10,
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size=15), # X axis title
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axis.title.y=element_text(size=12), # Y axis title
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axis.text.x=element_text(size=10,
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vjust=.5), # X axis text
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axis.text.y=element_text(size=10),
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legend.position = legend_position)+
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ggpubr::stat_pvalue_manual(stat.test,
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y.position = 1.05 * max(data[["Data_renamed"]][,number]),
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step.increase = step_increase,
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label.size = label_size,
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tip.length = tip_length,
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label = "p.adj.signif",
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size = 3.5,
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vjust = 0.05)
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ggsave(filename = paste(NAMES[number],"boxplot.png",collapse = ""),
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path=paste0(getwd(),"/boxplot"),
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width = fig_width,
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height = fig_height)}
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else if(significant_variable_only == F) {
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ggpubr::ggboxplot(data[["Data_renamed"]],
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x = "Group",
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y = colnames(data[["Data_renamed"]])[number],
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color = "Group",
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palette = ckey,
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add = "jitter",
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order = order,
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width = width)+
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scale_y_continuous(label=ecoflux::scientific_10x)+
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labs(title=NAMES[number],x =NULL, y = "Intensity")+
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theme_classic()+ ggplot2::theme(plot.title=element_text(size=15,
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face="bold",
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color="Black",
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hjust=0.5,
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lineheight=1.2), # title
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plot.subtitle=element_text(size=15,
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hjust=0.5), # subtitle
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plot.caption=element_text(size=15), # caption
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axis.title.x=element_text(vjust=10,
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size=15), # X axis title
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axis.title.y=element_text(size=12), # Y axis title
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axis.text.x=element_text(size=10,
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vjust=.5), # X axis text
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axis.text.y=element_text(size=10),
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legend.position = legend_position)
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ggsave(filename = paste(NAMES[number],"boxplot.png",collapse = ""),
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path=paste0(getwd(),"/boxplot"),
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width = fig_width,
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height = fig_height)}}}
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else if (length(unique(data[["Data_renamed"]][["Group"]]))==2) {
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p_val_data<-as.data.frame(p_val_data)
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if (asterisk=="t_test"){
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colnames(p_val_data)<-colnames(data[["Result"]])[1]
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}
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else if(asterisk == "u_test"){
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colnames(p_val_data)<-colnames(data[["Result"]])[2]
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}
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for (number in 1:nrow(p_val_data)){
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if (number == round(nrow(p_val_data)/4)){print("25% complete")}
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if (number == round(nrow(p_val_data)/3)){print("33% complete")}
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if (number == round(nrow(p_val_data)/2)){print("50% complete")}
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if (number == round(2*nrow(p_val_data)/3)){print("66% complete")}
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if (number == round(3*nrow(p_val_data)/4)){print("75% complete")}
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if (number == nrow(p_val_data)){print("100% complete")}
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df <- data_summary(data[["Data_renamed"]],
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varname = colnames(data[["Data_renamed"]])[number],
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groupnames = c("Group"))
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df <- df %>% plyr::mutate(ymax = len + SEM)
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colnames(df)[1] <- "Group"
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stat.test <- as.data.frame(matrix(data = NA, nrow = nrow(Comb),
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ncol = 2))
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stat.test[, 1:2] <- Comb
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if (asterisk == "Dunn") {
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rownames(stat.test) <- paste0(stat.test[, 1],
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" - ", stat.test[, 2])
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}
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else {
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rownames(stat.test) <- paste0(stat.test[, 1],
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"-", stat.test[, 2])
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}
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colnames(p_val_data) <- as.data.frame(strsplit(colnames(p_val_data),
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"___"))[1, ]
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t1 <- as.data.frame(t(as.data.frame(p_val_data[number,
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])))
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rownames(t1)<-colnames(p_val_data)
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t2 <- stat.test
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t3 <- merge(t2, t1, by = 0)
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stat.test <- t3[, 2:4]
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colnames(stat.test) <- c("group1", "group2",
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"p")
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stat.test <- stat.test %>% plyr::mutate(p.adj.signif = case_when(p >
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0.05 ~ "NS", p <= 0.05 & p > 0.01 ~ "*",
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p <= 0.01 ~ "**"))
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stat.test <- stat.test[stat.test$p.adj.signif !=
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"NS", ]
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if (length(stat.test>4)){
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ggpubr::ggboxplot(data[["Data_renamed"]],
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x = "Group",
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y = colnames(data[["Data_renamed"]])[number],
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color = "Group",
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palette = ckey,
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add = "jitter",
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order = order,
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width = width)+
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scale_y_continuous(label=ecoflux::scientific_10x)+
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labs(title=NAMES[number],x =NULL, y = "Intensity")+
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theme_classic()+ ggplot2::theme(plot.title=element_text(size=15,
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face="bold",
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color="Black",
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hjust=0.5,
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lineheight=1.2), # title
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plot.subtitle=element_text(size=15,
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hjust=0.5), # subtitle
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plot.caption=element_text(size=15), # caption
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axis.title.x=element_text(vjust=10,
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size=15), # X axis title
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axis.title.y=element_text(size=12), # Y axis title
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axis.text.x=element_text(size=10,
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vjust=.5), # X axis text
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axis.text.y=element_text(size=10),
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legend.position = legend_position,
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step.increase = step_increase,
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label.size = label_size,
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tip.length = tip_length)+
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ggpubr::stat_pvalue_manual(stat.test, y.position = 1.05 * max(data[["Data_renamed"]][,number]), step.increase = 0.1,label = "p.adj.signif",size = 3.5,vjust = 0.05)
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ggsave(filename = paste(NAMES[number],"boxplot.png",collapse = ""),
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path=paste0(getwd(),"/boxplot"),
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width = fig_width,
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height = fig_height)}
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else if(significant_variable_only == F) {
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ggpubr::ggboxplot(data[["Data_renamed"]],
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x = "Group",
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y = colnames(data[["Data_renamed"]])[number],
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color = "Group",
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palette = ckey,
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add = "jitter",
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order = order,
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width = width)+
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scale_y_continuous(label=ecoflux::scientific_10x)+
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labs(title=NAMES[number],x =NULL, y = "Intensity")+
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theme_classic()+ ggplot2::theme(plot.title=element_text(size=15,
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face="bold",
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color="Black",
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hjust=0.5,
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lineheight=1.2), # title
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plot.subtitle=element_text(size=15,
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hjust=0.5), # subtitle
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plot.caption=element_text(size=15), # caption
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axis.title.x=element_text(vjust=10,
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size=15), # X axis title
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axis.title.y=element_text(size=12), # Y axis title
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axis.text.x=element_text(size=10,
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vjust=.5), # X axis text
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axis.text.y=element_text(size=10),
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legend.position = legend_position)
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ggsave(filename = paste(NAMES[number],"boxplot.png",collapse = ""),
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path=paste0(getwd(),"/boxplot"),
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width = fig_width,
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height = fig_height)}}}
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)
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}

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