--- title: "Kean et al R code" author: "Iain RL Kean" date: "25/05/2021" output: pdf_document editor_options: chunk_output_type: console --- ```{r environment, include=FALSE} #Load packages into R environment, if package is not installed, initiates installation. if (!require("tidyverse")){ install.packages("tidyverse") library(tidyverse) } if (!require("ggfortify")){ install.packages("ggfortify") library(ggfortify) } if (!require("reshape2")){ install.packages("reshape2") library(reshape2) } if (!require("gridExtra")){ install.packages("gridExtra") library(gridExtra) } if (!require("vegan")){ install.packages("vegan") library(vegan) } if (!require("conover.test")){ install.packages("conover.test") library(conover.test) } if (!require("ggpubr")){ install.packages("ggpubr") library(ggpubr) } ``` ```{r Create output directory, include=FALSE} if(!dir.exists("~/Documents/Kean_2021")){ dir.create(file.path("~/Documents/", "Kean_2021")) } ``` ```{r statistical layers, include=FALSE} #Creates a dataframe from conover.test output to use with ggplot2 make_conover_layer <- function(df=NULL , group= NULL , method = "bh", step.increase = 0.1, text.adjust = 0.02, include.ns = F) { if (!require("conover.test")){ install.packages("conover.test") library(conover.test) } if (!require("tidyverse")){ install.packages("tidyverse") library("tidyverse") } con.df<- as.data.frame(conover.test::conover.test( x = df, g = group, method = method, altp = T)[2:5]) con.df <- con.df %>% separate(comparisons, c("x","xend")," - ") con.df$y <- max(df) lev <- levels(as.factor(group)) if (include.ns == T){ con.df$sig <- ifelse(con.df$altP.adjusted <= 0.05, "*",round(con.df$altP.adjusted, digits = 3)) } else{ con.df$sig <- ifelse(con.df$altP.adjusted <= 0.05, "*","NS") } con.df$sig <- ifelse(con.df$altP.adjusted <= 0.01, "**",con.df$sig) con.df$sig <- ifelse(con.df$altP.adjusted <= 0.001, "***",con.df$sig) con.df$tx <- match(con.df$x, lev) + (match(con.df$xend,lev) - match(con.df$x,lev))*0.5 if (include.ns == F){ con.df <- subset(con.df, as.numeric(con.df$altP.adjusted) <= 0.05 ) } if (nrow(con.df) >0){ for (i in 1:nrow(con.df)){ con.df$y[i] <- max(df,na.rm = T) + (max(df,na.rm = T)* i * step.increase ) con.df$ty[i] <- con.df$y[i] + (con.df$y[i] * text.adjust) } } con.df$yend <- con.df$y return(con.df) } ``` # Add the below line to your ggplot code + annotate("segment", x = df$x, xend = df$xend, y = df$y, yend=df$yend) + annotate("text", x = df$tx, y= df$ty, label = df$sig) # Example data("iris") iris.layer <- make_conover_layer(df=iris$Sepal.Length, group = iris$Species) iris.layer ggplot(iris, mapping = aes( x = Species, y = Sepal.Length)) + geom_boxplot() + annotate(geom = "segment", x=iris.layer$x, xend = iris.layer$xend, y= iris.layer$y, yend=iris.layer$yend) + annotate( geom = "text", y = iris.layer$ty, x= iris.layer$tx, label = iris.layer$sig ) ```{r Import bile acid data, include=FALSE} #Read file into dataframe ghici_full_3.df <- read.delim('~/Documents/Kean_2021/Kean_2021_data_table.csv', sep = ",", header = TRUE) #Add column for new date ranges ghici_full_3.df$DateRange2 <- ifelse(grepl("C", ghici_full_3.df$Sample_ID, ignore.case = T), "Control", "X") ghici_full_3.df$DateRange2 <- ifelse( as.numeric(ghici_full_3.df$DayspostPICU) <3.5 & ghici_full_3.df$DayspostPICU != "Control", "d1-3", ghici_full_3.df$DateRange2) ghici_full_3.df$DateRange2 <- ifelse( as.numeric(ghici_full_3.df$DayspostPICU) >=3.5 & as.numeric(ghici_full_3.df$DayspostPICU) <=7.0, "d4-7", ghici_full_3.df$DateRange2) ghici_full_3.df$DateRange2 <- ifelse( as.numeric(ghici_full_3.df$DayspostPICU) >7.0 ,"d8-10", ghici_full_3.df$DateRange2) ghici_full_3.df$DateRange2 <- ifelse( is.na(ghici_full_3.df$DateRange2) , "d1-3", ghici_full_3.df$DateRange2) ghici_full_3.df$DateRange2 <- ifelse(grepl("C", ghici_full_3.df$Sample_ID, ignore.case = T), "Control",ghici_full_3.df$DateRange2) ghici_full_3.df$secBA <- ghici_full_3.df$Deoxycholic_Acid + ghici_full_3.df$Lithocholic_acid + ghici_full_3.df$Isolithocholic_Acid + ghici_full_3.df$Ursodeoxycholic_acid + ghici_full_3.df$X3a.Hydroxy.12_Ketolithocholic_Acid + ghici_full_3.df$X3a.Hydroxy.12_Ketolithocholic_Acid.1 + ghici_full_3.df$Taurohyocholic_Acid + ghici_full_3.df$Glycoursodeoxycholic_Acid ghici_full_3.df$priBA <- ghici_full_3.df$Cholic_acid + ghici_full_3.df$Chenodeoxycholic_Acid + ghici_full_3.df$Glycochenodeoxycholic_Acid + ghici_full_3.df$Taurocholic_Acid #Subset of dataframe with bile acids by.df<- subset(ghici_full_3.df, ghici_full_3.df$Cholic_acid >0)[,c(1:32,216:218)] by.df <-droplevels(by.df) ``` ```{r Prepare taxanomic dataframes , include=FALSE}} genus.df <- subset(ghici_full_3.df, rowSums(ghici_full_3.df[,57:215]) > 0)[,c(34:216)] colnames(ghici_full_3.df)[216] nrow(genus.df) genus.df$Shannon <- diversity(genus.df[,c(24:182)], index = "shannon") genus.df$first_sample <- ifelse(genus.df$first_sample =="first_sample ","First",genus.df$first_sample) genus.df$first_sample <- ifelse(genus.df$first_sample =="second_sample","Second",genus.df$first_sample) genus.df$first_sample <- ifelse(genus.df$first_sample =="third_sample","Third",genus.df$first_sample) genus.df$first_sample <- ifelse(genus.df$first_sample =="control","Control",genus.df$first_sample) genus.df$infection <- ifelse(grepl(x = genus.df$diagnosis_group1 , pattern = "infection",ignore.case = T),"Infection",ifelse(grepl(x = genus.df$diagnosis_group1 , pattern = "control",ignore.case = T), "Control","Other")) genus.df$diagnosis_group1 <- ifelse(genus.df$diagnosis_group1 =="resp_infection","Resp Infection",genus.df$diagnosis_group1) genus.df$diagnosis_group1 <- ifelse(genus.df$diagnosis_group1 =="control","Control",genus.df$diagnosis_group1) genus.df$diagnosis_group2 <- ifelse(genus.df$diagnosis_group2 =="lung","Resp Infection" , ifelse(genus.df$diagnosis_group2 =="control","Control","No Resp Infection")) genus.df$amo <- ifelse( grepl("amo" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins genus.df$aug <- ifelse( grepl("aug" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins #TAZOBACTAM genus.df$azi <- ifelse( grepl("azi" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#macorlide genus.df$benz <- ifelse( grepl("benz" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) #penicillins genus.df$cef <- ifelse( grepl("cef" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) #cephalosporin genus.df$cet <- ifelse( grepl("cet" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#cephalosporin genus.df$chl <- ifelse( grepl("chl" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) #Amphenicols genus.df$cip <- ifelse( grepl("cip" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) #quinolone genus.df$clar <- ifelse( grepl("clar" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#macorlide genus.df$clin <- ifelse( grepl("clin" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#Lincosamide genus.df$coa <- ifelse( grepl("coa" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins #TAZOBACTAM genus.df$ery <- ifelse( grepl("ery" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#macorlide genus.df$flu <- ifelse( grepl("flu" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) genus.df$gent <- ifelse( grepl("gent" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#Aminoglycoside genus.df$met <- ifelse( grepl("met" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins genus.df$pen <- ifelse( grepl("pen" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins genus.df$pip <- ifelse( grepl("pip" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#penicillins genus.df$tax <- ifelse( grepl("tax" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#TAZOBACTAM genus.df$taz <- ifelse( grepl("taz" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#TAZOBACTAM genus.df$tei <- ifelse( grepl("tei" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#glycopeptide genus.df$tob <- ifelse( grepl("tob" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#Aminoglycoside genus.df$van <- ifelse( grepl("van" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0)#glycopeptide genus.df$unknown <- ifelse( grepl("unknown" , genus.df$antibiotic_type, ignore.case = TRUE), 1, 0) genus.df$abNum <- rowSums(genus.df[, 186:208]) genus.df$RAB2 <- genus.df$Alistipes+genus.df$Bacteroides+ genus.df$Bifidobacterium+ genus.df$Coprococcus+ genus.df$Desulfovibrio+ genus.df$Faecalibacterium+ genus.df$Parabacteroides+ genus.df$Roseburia+ genus.df$Ruminococcus+ genus.df$Subdoligranulum genus.df$Sex_. # Infer location from ventilation free days genus.df$Location <- ifelse( genus.df$group_patient =="patient" , ifelse( ((28 - as.numeric(genus.df$PICU_free_days) )- (as.numeric(genus.df$day_sample))) >=0, "PICU","General"), "Control") genus.df$Location[6] <- "PICU" genus.df$Location <- factor(genus.df$Location,levels = c("Control","PICU","General") ) droplevels(genus.df$Location) #Create distance matrix of taxanomic data tc.mat <- as.matrix.data.frame(genus.df[,24:182]) tc.dist <- vegdist(tc.mat) tc.mds <- metaMDS(tc.dist, scale.=T) #Add identifying data to NMDS dataframe tc2.dat <- as.data.frame(tc.mds$points) tc2.dat$Samlpe_num <- genus.df$Sample_num tc2.dat$GHICI_number<- genus.df$GHICI_num tc2.dat$DateRange2 <- genus.df$DateRange2 tc2.dat$Sex <- genus.df$Sex summary(as.factor(tc2.dat$DateRange2)) subset(tc2.dat, tc2.dat$DateRange2 == "Control") tc2.con <- subset(tc2.dat, tc2.dat$DateRange2 == "Control") ggplot(tc2.con, mapping = aes(x= MDS1, y=MDS2, colour = Sex)) + geom_point() + stat_ellipse(level = 0.6) c.df <- subset(genus.df, genus.df$DateRange2 == "Control") TukeyHSD(betadisper(vegdist(c.df[,24:182]), group = c.df$Sex)) ``` ```{r patient data} weight.df <- subset(ghici_full_3.df, !is.na(ghici_full_3.df$weight_kg)) conover.test(x=weight.df$weight_kg, g = weight.df$Patient_0no1yes) summary(subset(weight.df, weight.df$Patient_0no1yes ==1)$weight_kg) summary(subset(weight.df, weight.df$Patient_0no1yes ==0)$weight_kg) #ggplot(weight.df, mapping = aes(x = as.factor(Patient_0no1yes), y = weight_kg)) + geom_boxplot(notch = T)+ xlab("Patient No:0, Yes:1") + ylab("Weight (kg)") age.df <- subset(ghici_full_3.df, !is.na(ghici_full_3.df$age_months)) conover.test(x=age.df$age_months, g = age.df$Patient_0no1yes) summary(subset(age.df, age.df$Patient_0no1yes ==1)$age_months/12) summary(subset(age.df, age.df$Patient_0no1yes ==0)$age_months/12) #ggplot(age.df, mapping = aes(x = as.factor(Patient_0no1yes), y = age_months/12)) + geom_boxplot(notch = T) + xlab("Patient No:0, Yes:1")+ ylab("Age (years)") summary(as.factor(ghici_full_3.df$Primary_Organ_failure)) sex.df <- subset(ghici_full_3.df, !is.na(ghici_full_3.df$Sex)) conover.test(x=age.df$age_months, g = age.df$Patient_0no1yes) summary(as.factor(subset(age.df, age.df$Patient_0no1yes ==1)$Sex)) summary(as.factor(subset(age.df, age.df$Patient_0no1yes ==0)$Sex)) ``` ```{r WAZ calculation eval=FALSE, include=FALSE} # Code for reference only. Data table has full and correct WAZ including values missed by calculator install.packages("zscorer") library("zscorer") colnames(ghici_full_3.df)[33] ghici_full_3.df$sex <- ifelse(ghici_full_3.df$Sex == "M", 1, ifelse(ghici_full_3.df$Sex == "F", 2, 0)) ghici_full_3.df$age_days <- ghici_full_3.df$age_months*(365.23/12) ghici_full_3.df$wafz <- addWGSR(data = ghici_full_3.df, sex = "sex" , firstPart = "weight_kg", secondPart = "age_days",index = "wfa", )$wfaz #write_delim(ghici_full_3.df ,"KEAN_2021_data_table_2.csv", delim = ",") ``` ```{r Figure 1} pric <- make_conover_layer(df = (by.df$Cholic_acid+by.df$Chenodeoxycholic_Acid+by.df$Glycochenodeoxycholic_Acid+by.df$Taurocholic_Acid)/rowSums(by.df[,14:32]), group = by.df$DateRange2, method = "bh") pri.plot <- ggplot(by.df, aes(x= DateRange2 , y = ((Cholic_acid+Chenodeoxycholic_Acid+Glycochenodeoxycholic_Acid+Taurocholic_Acid)/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = pric$x, xend = pric$xend, y = pric$y, yend = pric$yend) + annotate( "text", x= pric$tx, y = pric$ty, label = pric$sig) + scale_y_continuous() + ylab('RC of Primary Bile Acids') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="a")#, axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.title.y = element_text(size = 15) , axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) secc <- make_conover_layer(df=((by.df$Deoxycholic_Acid+by.df$Lithocholic_acid+by.df$Isolithocholic_Acid+by.df$Ursodeoxycholic_acid+by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid`+by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid.1`+by.df$Taurohyocholic_Acid+by.df$Glycoursodeoxycholic_Acid)/rowSums(by.df[,14:32])),group=by.df$DateRange2, method = "bh" ) sec.plot <- ggplot(by.df, aes(x= DateRange2 , y = ((Deoxycholic_Acid+Lithocholic_acid+Isolithocholic_Acid+Ursodeoxycholic_acid +`X3a.Hydroxy.12_Ketolithocholic_Acid`+`X3a.Hydroxy.12_Ketolithocholic_Acid.1`+Taurohyocholic_Acid+Glycoursodeoxycholic_Acid)/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = secc$x, xend = secc$xend, y = secc$y, yend = secc$yend) + annotate( "text", x= secc$tx, y = secc$ty, label = secc$sig) + scale_y_continuous() + ylab('RC of Secondary Bile Acids') + geom_jitter (aes( colour = DateRange2), width =0.2, , size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="b") # ,axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.title.y = element_text(size = 15) , axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) fig2.b crc <- make_conover_layer((by.df$Cholic_acid)/(by.df$Chenodeoxycholic_Acid), by.df$DateRange2, method = "bh") chen_ratio.plot <- ggplot(by.df, aes(x= DateRange2 , y = (Cholic_acid/Chenodeoxycholic_Acid), fill=DateRange2)) + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + theme_bw() + annotate("segment", x = crc$x, xend = crc$xend, y = crc$y, yend = crc$yend) + annotate( "text", x= crc$tx, y = crc$ty, label = crc$sig)+ scale_y_continuous() + ylab('CA:CDCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="c") #,axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title.y = element_text(size = 15) ,axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) ratioc <-make_conover_layer((by.df$Cholic_acid+by.df$Chenodeoxycholic_Acid+by.df$Glycochenodeoxycholic_Acid+by.df$Taurocholic_Acid)/(by.df$Deoxycholic_Acid+by.df$Lithocholic_acid+by.df$Isolithocholic_Acid+by.df$Ursodeoxycholic_acid+by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid`+by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid.1`+by.df$Taurohyocholic_Acid+by.df$Glycoursodeoxycholic_Acid),by.df$DateRange2, method = "bh") ratio.plot <- ggplot(by.df, aes(x= DateRange2 , y = (Cholic_acid+Chenodeoxycholic_Acid+Glycochenodeoxycholic_Acid+ Taurocholic_Acid)/(Deoxycholic_Acid+ Lithocholic_acid+ Isolithocholic_Acid+Ursodeoxycholic_acid+`X3a.Hydroxy.12_Ketolithocholic_Acid`+`X3a.Hydroxy.12_Ketolithocholic_Acid.1`+Taurohyocholic_Acid+Glycoursodeoxycholic_Acid), fill=DateRange2)) + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + theme_bw() + annotate("segment", x = ratioc$x, xend = ratioc$xend, y = ratioc$y, yend = ratioc$yend) + annotate( "text", x= ratioc$tx, y = ratioc$ty, label = ratioc$sig)+ scale_y_continuous() + ylab(expression(paste("Ratio of 1",degree," to 2",degree," Bile Acids"))) + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="d") #,axis.title.x=element_blank(), size = 15, hjust = 0.5), axis.title.y = element_text(size = 15) , axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) ratio.plot cdc <- make_conover_layer((by.df$Cholic_acid)/(by.df$Deoxycholic_Acid), by.df$DateRange2, method ="bh") chol_deox_ratio.plot <- c<- ggplot(by.df, aes(x= DateRange2 , y = (Cholic_acid/Deoxycholic_Acid), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") #,axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.title.y = element_text(size = 15) , axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) clc <- make_conover_layer((by.df$Chenodeoxycholic_Acid)/(by.df$Lithocholic_acid+by.df$Isolithocholic_Acid), by.df$DateRange2, method = "by") chen_lith_ratio.plot <- ggplot(by.df, aes(x= DateRange2 , y = (Chenodeoxycholic_Acid/(Lithocholic_acid+Isolithocholic_Acid)), fill=DateRange2))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = clc$x, xend = clc$xend, y = clc$y, yend = clc$yend) + annotate( "text", x= clc$tx, y = clc$ty, label = clc$sig) + scale_y_continuous() + ylab('CDCA:LCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="f") # ,axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.title.y = element_text(size = 15) , axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="f") fig1 <- grid.arrange(pri.plot, sec.plot ,chen_ratio.plot, ratio.plot, chol_deox_ratio.plot, chen_lith_ratio.plot, nrow = 2) fig1 ggsave( "~/Documents/Kean_2021/Kean_2021_Figure_1.png",plot = fig1, height = 120 , width = 170, units = "mm", dpi = 600) ``` ```{r} by.df cdc <- make_conover_layer((by.df$Cholic_acid+by.df$Chenodeoxycholic_Acid)/(by.df$Taurohyocholic_Acid + by.df$Taurocholic_Acid + by.df$Glycochenodeoxycholic_Acid ), by.df$DateRange2, method ="bh") rowSums(by.df[,14:32]) ggplot(by.df, aes(x= DateRange2 , y = ((Cholic_acid +Chenodeoxycholic_Acid )/(Taurohyocholic_Acid +Taurocholic_Acid +Glycochenodeoxycholic_Acid)), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") cdc <- make_conover_layer((by.df$Lithocholic_acid+by.df$Deoxycholic_Acid)/(by.df$Taurohyocholic_Acid + by.df$Taurocholic_Acid + by.df$Glycochenodeoxycholic_Acid ), by.df$DateRange2, method ="bh") ggplot(by.df, aes(x= DateRange2 , y = ((Lithocholic_acid +Deoxycholic_Acid )/(Taurohyocholic_Acid +Taurocholic_Acid +Glycochenodeoxycholic_Acid)), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") cdc <- make_conover_layer((by.df$Lithocholic_acid+by.df$Deoxycholic_Acid)/(rowSums(by.df[,14:32])), by.df$DateRange2, method ="bh") ggplot(by.df, aes(x= DateRange2 , y = ((Lithocholic_acid +Deoxycholic_Acid )/(rowSums(by.df[,14:32]))), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") cdc <- make_conover_layer((by.df$Taurohyocholic_Acid+by.df$Taurocholic_Acid)/( by.df$Glycochenodeoxycholic_Acid ), by.df$DateRange2, method ="bh") ggplot(by.df, aes(x= DateRange2 , y = ((Taurohyocholic_Acid +Taurocholic_Acid )/(Glycochenodeoxycholic_Acid)), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") summary(by1.df$Taurohyocholic_Acid/rowSums(by1.df[,14:32])) cdc <- make_conover_layer((by.df$Taurohyocholic_Acid+by.df$Taurocholic_Acid + by.df$Glycochenodeoxycholic_Acid)/(rowSums(by.df[,14:32])), by.df$DateRange2, method ="bh") ggplot(by.df, aes(x= DateRange2 , y = ((Taurohyocholic_Acid +Taurocholic_Acid +Glycochenodeoxycholic_Acid)/(rowSums(by.df[,14:32]))), fill=DateRange2)) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = cdc$x, xend = cdc$xend, y = cdc$y, yend = cdc$yend) + annotate( "text", x= cdc$tx, y = cdc$ty, label = cdc$sig) + scale_y_continuous() + ylab('CA:DCA') + geom_jitter (aes( colour = DateRange2), width =0.2, size = 0.5) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none" ,axis.title.x=element_blank() , axis.text.y.left = element_text(angle = 90)) +labs(tag="e") subset(by.df, by.df$DateRange2 =="d1-3") -> by1.df summary((by1.df$Taurohyocholic_Acid+by1.df$Taurocholic_Acid + by1.df$Glycochenodeoxycholic_Acid)/(rowSums(by1.df[,14:32]))) ``` ```{r Figure S1} ba1c <- make_conover_layer(df =by.df$`X3a.Hydroxy.6.7.DiketoCholanic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 ,method= "bh") figS1.1 <- ggplot(by.df, aes(x= DateRange2 , y = (`X3a.Hydroxy.6.7.DiketoCholanic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba1c$x, xend = ba1c$xend, y = ba1c$y, yend=ba1c$yend) + annotate("text", x = ba1c$tx, y= ba1c$ty, label = ba1c$sig) + scale_y_continuous() + ylab(expression(paste('RC of 3',alpha,'-OH,6,7-diKClA'))) + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="a") ba2c <- make_conover_layer(df =by.df$Taurohyocholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.2 <- ggplot(by.df, aes(x= DateRange2 , y = (Taurohyocholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba2c$x, xend = ba2c$xend, y = ba2c$y, yend=ba2c$yend) + annotate("text", x = ba2c$tx, y= ba2c$ty, label = ba2c$sig) + scale_y_continuous() + ylab('RC of THCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="b") figS1.2 ba3c <- make_conover_layer(df =by.df$Glycoursodeoxycholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.3 <- ggplot(by.df, aes(x= DateRange2 , y = (Glycoursodeoxycholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba3c$x, xend = ba3c$xend, y = ba3c$y, yend=ba3c$yend) + annotate("text", x = ba3c$tx, y= ba3c$ty, label = ba3c$sig) + scale_y_continuous() + ylab('RC of GUDCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="c") figS1.2 ba4c <- make_conover_layer(df =by.df$`X3_Dehydrocholic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.4 <- ggplot(by.df, aes(x= DateRange2 , y = (`X3_Dehydrocholic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba4c$x, xend = ba4c$xend, y = ba4c$y, yend=ba4c$yend) + annotate("text", x = ba4c$tx, y= ba4c$ty, label = ba4c$sig) + scale_y_continuous() + ylab('RC of 3-DHCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="d") ba5c <- make_conover_layer(df =by.df$`X3.12.Diketocholanic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.5 <- ggplot(by.df, aes(x= DateRange2 , y = (`X3.12.Diketocholanic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba5c$x, xend = ba5c$xend, y = ba5c$y, yend=ba5c$yend) + annotate("text", x = ba5c$tx, y= ba5c$ty, label = ba5c$sig) + scale_y_continuous() + ylab('RC of 3,12-diKClA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="e") ba6c <- make_conover_layer(df =by.df$Ursodeoxycholic_acid/by.df$Chenodeoxycholic_Acid, group= by.df$DateRange2 , method ="bh") ggplot(by.df, aes(x= DateRange2 , y = (Ursodeoxycholic_acid/Chenodeoxycholic_Acid) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba6c$x, xend = ba6c$xend, y = ba6c$y, yend=ba6c$yend) + annotate("text", x = ba6c$tx, y= ba6c$ty, label = ba6c$sig) + scale_y_continuous() + ylab('UDCA:CDCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="f") ba6c <- make_conover_layer(df =by.df$Ursodeoxycholic_acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.6 <- ggplot(by.df, aes(x= DateRange2 , y = (Ursodeoxycholic_acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba6c$x, xend = ba6c$xend, y = ba6c$y, yend=ba6c$yend) + annotate("text", x = ba6c$tx, y= ba6c$ty, label = ba6c$sig) + scale_y_continuous() + ylab('RC of UDCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="f") ba7c <- make_conover_layer(df =by.df$`X12_Dehydrocholic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.7 <- ggplot(by.df, aes(x= DateRange2 , y = (`X12_Dehydrocholic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba7c$x, xend = ba7c$xend, y = ba7c$y, yend=ba7c$yend) + annotate("text", x = ba7c$tx, y= ba7c$ty, label = ba7c$sig) + scale_y_continuous() + ylab('RC of 12-DHCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="g") ba8c <- make_conover_layer(df =by.df$Glycochenodeoxycholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.8 <- ggplot(by.df, aes(x= DateRange2 , y = (Glycochenodeoxycholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba8c$x, xend = ba8c$xend, y = ba8c$y, yend=ba8c$yend) + annotate("text", x = ba8c$tx, y= ba8c$ty, label = ba8c$sig) + scale_y_continuous() + ylab('RC of GCDCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="h") figS1.8 ba9c <- make_conover_layer(df =by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.9 <- ggplot(by.df, aes(x= DateRange2 , y = (`X3a.Hydroxy.12_Ketolithocholic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba9c$x, xend = ba9c$xend, y = ba9c$y, yend=ba9c$yend) + annotate("text", x = ba9c$tx, y= ba9c$ty, label = ba9c$sig) + scale_y_continuous() + ylab(expression(paste('RC of 3',alpha,'-H,12-KLCA'))) + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="i") ba10c <- make_conover_layer(df =by.df$Isolithocholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.10 <- ggplot(by.df, aes(x= DateRange2 , y = (Isolithocholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba10c$x, xend = ba10c$xend, y = ba10c$y, yend=ba10c$yend) + annotate("text", x = ba10c$tx, y= ba10c$ty, label = ba10c$sig) + scale_y_continuous() + ylab('RC of ILCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="j") ba11c <- make_conover_layer(df =by.df$Chenodeoxycholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.11 <- ggplot(by.df, aes(x= DateRange2 ,y = (Chenodeoxycholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba11c$x, xend = ba11c$xend, y = ba11c$y, yend=ba11c$yend) + annotate("text", x = ba11c$tx, y= ba11c$ty, label = ba11c$sig) + scale_y_continuous() + ylab('RC of CDCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 10, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="k") ba12c <- make_conover_layer(df =by.df$`X5ß.Cholanic_Acid.3ß._12a.diol`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.12 <- ggplot(by.df, aes(x= DateRange2 , y = (`X5ß.Cholanic_Acid.3ß._12a.diol`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba12c$x, xend = ba12c$xend, y = ba12c$y, yend=ba12c$yend) + annotate("text", x = ba12c$tx, y= ba12c$ty, label = ba12c$sig)+ ylab(expression(paste('RC of 5',beta,'-ClA,3',beta,',12',alpha,'-diol'))) + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 10, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="l") ba13c <- make_conover_layer(df =by.df$`X3.Ketocholanic_Acid`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.13 <- ggplot(by.df, aes(x= DateRange2 , y = (`X3.Ketocholanic_Acid`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba13c$x, xend = ba13c$xend, y = ba13c$y, yend=ba13c$yend) + annotate("text", x = ba13c$tx, y= ba13c$ty, label = ba13c$sig) + scale_y_continuous() + ylab('RC of 3-KClA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="m") ba14c <- make_conover_layer(df =by.df$Lithocholic_acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.14 <- ggplot(by.df, aes(x= DateRange2 , y = (Lithocholic_acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba14c$x, xend = ba14c$xend, y = ba14c$y, yend=ba14c$yend) + annotate("text", x = ba14c$tx, y= ba14c$ty, label = ba14c$sig) + scale_y_continuous() + ylab('RC of LCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="n") ba15c <- make_conover_layer(df =by.df$Deoxycholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.15 <- ggplot(by.df, aes(x= DateRange2 , y = (Deoxycholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba15c$x, xend = ba15c$xend, y = ba15c$y, yend=ba15c$yend) + annotate("text", x = ba15c$tx, y= ba15c$ty, label = ba15c$sig) + scale_y_continuous() + ylab('RC of DCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="o") ba16c <- make_conover_layer(df =by.df$Cholic_acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.16 <- ggplot(by.df, aes(x= DateRange2 , y = (Cholic_acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba16c$x, xend = ba16c$xend, y = ba16c$y, yend=ba16c$yend) + annotate("text", x = ba16c$tx, y= ba16c$ty, label = ba16c$sig) + scale_y_continuous() + ylab('RC of CA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="p") ba17c <- make_conover_layer(df =by.df$`X23.nor.5b.Cholanic_Acid.3a._12a.diol`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.17 <- ggplot(by.df, aes(x= DateRange2 , y = (`X23.nor.5b.Cholanic_Acid.3a._12a.diol`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba17c$x, xend = ba17c$xend, y = ba17c$y, yend=ba17c$yend) + annotate("text", x = ba17c$tx, y= ba17c$ty, label = ba17c$sig) + scale_y_continuous() + ylab(expression(paste('RC of 23 nor-,5',beta,'-ClA,3',alpha,',12',alpha,'-diol'))) + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="q") ba18c <- make_conover_layer(df =by.df$`X3a.Hydroxy.12_Ketolithocholic_Acid.1`/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.18 <-ggplot(by.df, aes(x= DateRange2 , y = (`X3a.Hydroxy.12_Ketolithocholic_Acid.1`/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba18c$x, xend = ba18c$xend, y = ba18c$y, yend=ba18c$yend) + annotate("text", x = ba18c$tx, y= ba18c$ty, label = ba18c$sig) + scale_y_continuous() + ylab(expression(paste('RC of 3',alpha,'-H,12-KLCA 2'))) + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 10, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="r") ba19c <- make_conover_layer(df =by.df$Taurocholic_Acid/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.19 <- ggplot(by.df, aes(x= DateRange2 , y = (Taurocholic_Acid/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba19c$x, xend = ba19c$xend, y = ba19c$y, yend=ba19c$yend) + annotate("text", x = ba19c$tx, y= ba19c$ty, label = ba19c$sig) + scale_y_continuous() + ylab('RC of TCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="s") figS1.19 figS1 <- grid.arrange(figS1.1,figS1.2, figS1.3, figS1.4, figS1.5, figS1.6, figS1.7, figS1.8,figS1.9, figS1.10, figS1.11, figS1.12, figS1.13, figS1.14, figS1.15, figS1.16, figS1.17, figS1.18, figS1.19, nrow=4) ggsave("~/Documents/Kean_2021/Kean_2021_Figure_S1.eps", plot = figS1, width =470, height = 280 ,units = "mm", dpi = 300) ``` ```{r} ba2c <- make_conover_layer(df =(by.df$Taurohyocholic_Acid + by.df$Glycochenodeoxycholic_Acid = by.df$Taurohyocholic_Acid)/rowSums(by.df[,14:32]), group= by.df$DateRange2 , method ="bh") figS1.2 <- ggplot(by.df, aes(x= DateRange2 , y = (Taurohyocholic_Acid)/rowSums(by.df[,14:32], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = ba2c$x, xend = ba2c$xend, y = ba2c$y, yend=ba2c$yend) + annotate("text", x = ba2c$tx, y= ba2c$ty, label = ba2c$sig) + scale_y_continuous() + ylab('RC of THCA') + geom_jitter (aes( colour = DateRange2), width =0.2) + scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2',"forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange',"darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="b") ``` ```{r Figure 2} #Shanon index fig2a.con <- make_conover_layer(group = genus.df$DateRange2, df = genus.df$Shannon, method = "bh") fig2.a <- ggplot( genus.df, mapping = aes(x = DateRange2, y = Shannon, fill = DateRange2))+ theme_bw()+ geom_violin(draw_quantiles = c(0.25,0.5,0.75))+ scale_fill_manual( values = c('lightblue','firebrick','goldenrod',"forestgreen",'firebrick','goldenrod',"forestgreen"))+ annotate("segment", x= fig2a.con$x, xend = fig2a.con$xend, y= fig2a.con$y, yend = fig2a.con$yend) + annotate("text" , x = fig2a.con$tx, y = fig2a.con$ty, label = fig2a.con $sig)+labs(tag="a")+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, hjust = 0.5) , axis.text.x.bottom = element_text( hjust = 0.5)) tc2.dat %>% outer_join(ghici_full_3.df$Sex_.) # Diversity fig2.b <-ggplot( tc2.dat, mapping = aes( x= MDS1, y = MDS2, colour = Sex) ) +theme_bw()+ geom_point(size = 0.5) +stat_ellipse(level =0.6) + scale_colour_manual( values = c('darkblue','firebrick','goldenrod3',"forestgreen")) + theme(legend.position="bottom", axis.text.y.left = element_text(angle = 90, hjust = 0.5), axis.text.x= element_text( hjust = 0.7), legend.text = element_text(size = 7), legend.title = element_blank() ) +labs(tag="b", colour ="Group") #fig2.b TukeyHSD(betadisper(tc.dist, group= tc2.dat$Sex)) fig2 <- grid.arrange(fig2.a, fig2.b ,nrow= 2) ggsave(filename = "~/Documents/Kean_2021/Kean_2021_Figure_2.eps", plot = fig2, width = 85, height = 170, units = "mm", dpi = 300) tc.beta2 <- betadisper(tc.dist, genus.df$DateRange2, type = "centroid") TukeyHSD(tc.beta2) ``` ```{r Figure 3} #Truncated family level taxonomy derived from SILVA138.1 database. family.df <- read.delim('~/Documents/Kean_2021/Kean_2021_family_taxonomy.csv', sep=",") family.df$DateRange2 <- ifelse( family.df$day_sample >=1 & family.df$day_sample <=3, "d1-3", "x") family.df$DateRange2 <- ifelse( family.df$day_sample >=4 & family.df$day_sample <=7, "d4-7", family.df$DateRange2) family.df$DateRange2 <- ifelse( family.df$day_sample >7 ,"d8-10", family.df$DateRange2) family.df$DateRange2 <- ifelse( family.df$day_sample <=0, "Control", family.df$DateRange2) family.df$infection <- genus.df$infection #melt faily dataframe for plotting fam.melt = melt(family.df[,c(1:2,27,3:4,6:26)]) fig3 <- ggplot( data = fam.melt, mapping = aes( x = GHICI_num, y = value, fill = variable)) + geom_col( position="fill", colour = "grey50" ) +theme_bw()+ theme(legend.title = element_text( face= "bold", size = 10), axis.title.x=element_blank() ,legend.text = element_text(size = 6, face="italic"), axis.text.x=element_text( angle = 300, hjust = 0, vjust = 0.5, size = 5.5), axis.text.y = element_text(angle = 90, hjust = 0.5), legend.key.size = unit(0.5,"line")) + facet_grid(~ DateRange2, scales= "free_x", space = "free_x", )+ ylab("Relative Proportion") + scale_fill_manual(name = "Family" , values=c('#e31a1c','#fb9a99', '#a6cee3','#1f78b4', '#fdbf6f','#ff7f00', '#33a02c','#b2df8a', '#cab2d6' ,'#6a3d9a', "grey25",'#6a3d9a','#cab2d6' ,'#ff7f00','#fdbf6f', '#e31a1c','#fb9a99' ,'#33a02c','#b2df8a','#1f78b4','#a6cee3')) + scale_y_continuous(expand = c(0,0)) + guides(fill = guide_legend(ncol = 1)) fig3 ggsave(filename = "~/Documents/Kean_2021/Kean_2021_Figure_3.eps", plot = fig3, width = 250, height = 150, units = "mm", dpi = 300) ``` ```{r Figure 4} raballc <-make_conover_layer(df = genus.df$RAB2/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 , method = "bh" ) fig4.a <- ggplot(genus.df, aes(x= DateRange2 , y = ((RAB2)/rowSums(genus.df[,24:182], na.rm= TRUE) ), fill = DateRange2 ) ) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = raballc$x, xend = raballc$xend, y = raballc$y, yend=raballc$yend) + annotate("text", x = raballc$tx, y= raballc$ty, label = raballc$sig) + scale_y_continuous() + ylab('Proportion of RAB') + geom_jitter (aes( colour = DateRange2), width = 0.2, size = 0.5)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen','firebrick', 'goldenrod2', "forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen','red','darkorange', "darkgreen"))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, hjust = 0.5), axis.text.x.bottom = element_text( hjust = 0.5)) +labs(tag="a") c.l <-make_conover_layer(df = family.df$Lachnospiraceae/rowSums(family.df[,6:26]), group= family.df$DateRange2 , method = "bh" ) fig4.b <- ggplot(family.df, aes(x= DateRange2 , y = (`Lachnospiraceae`/rowSums(family.df[,6:26], na.rm= TRUE)) , fill = DateRange2 ))+ theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = c.l$x, xend = c.l$xend, y = c.l$y, yend=c.l$yend) + annotate("text", x = c.l$tx, y= c.l$ty, label = c.l$sig) + scale_y_continuous() + xlab('Days Post PICU Admission') + ylab(expression('Prop. of '~italic('Lachnospiraceae'))) + geom_jitter (aes( colour = DateRange2) , width = 0.2, size = 0.5)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2', "forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange', "darkgreen")) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, hjust = 0.5) , axis.text.x.bottom = element_text( hjust = 0.5)) +labs(tag="b") fig4 <- grid.arrange(fig4.a , fig4.b, nrow =2) ggsave("~/Documents/Kean_2021/Kean_2021_Figure_4.eps", plot= fig4, width = 85, height = 120, units = "mm", dpi = 300) ``` ```{r} raballc <-make_conover_layer(df = genus.df$Bacteroides/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 , method = "bh" ) ggplot(genus.df, aes(x= DateRange2 , y = (Bacteroides/rowSums(genus.df[,24:182], na.rm= TRUE) ), fill = DateRange2 ) ) + theme_bw()+ geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = raballc$x, xend = raballc$xend, y = raballc$y, yend=raballc$yend) + annotate("text", x = raballc$tx, y= raballc$ty, label = raballc$sig) + scale_y_continuous() + ylab('Proportion of RAB') + geom_jitter (aes( colour = DateRange2), width = 0.2, size = 0.5)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen','firebrick', 'goldenrod2', "forestgreen")) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen','red','darkorange', "darkgreen"))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, hjust = 0.5), axis.text.x.bottom = element_text( hjust = 0.5)) +labs(tag="a") ``` ```{r Figur S2} loc.con <- make_conover_layer(group = genus.df$first_sample, df = (genus.df$RAB2/rowSums(genus.df[,24:182])), method = "bh") figS2.a <-ggplot(genus.df, aes(x= first_sample , y = (`RAB2`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = first_sample )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = loc.con$x, xend = loc.con$xend, y = loc.con$y, yend=loc.con$yend) + annotate("text", x = loc.con$tx, y= loc.con$ty, label = loc.con$sig) + scale_y_continuous() + xlab('Sample number') + ylab(expression('Proportion of RAB')) + geom_jitter (aes( colour = DateRange2, shape = Location))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 13, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="a") family.df$diagnosis_group1 <- genus.df$diagnosis_group1 family.df$diagnosis_group2 <- genus.df$diagnosis_group2 loc.con <- make_conover_layer(group = family.df$diagnosis_group1, df = (genus.df$RAB2/rowSums(genus.df[,24:182])), method = "bh") figS2.b <- ggplot(genus.df, aes(x= diagnosis_group1 , y = (`RAB2`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = diagnosis_group1 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = loc.con$x, xend = loc.con$xend, y = loc.con$y, yend=loc.con$yend) + annotate("text", x = loc.con$tx, y= loc.con$ty, label = loc.con$sig) + scale_y_continuous() + xlab('Primary Diagnosis') + ylab(expression('Proportion of RAB')) + geom_jitter (aes( colour = diagnosis_group1))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen',"darkblue","pink")) + scale_colour_manual(values=c('darkblue','red',"darkorange",'darkgreen',"royalblue","purple"))+ theme(legend.position = "none", axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 10, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="b") loc.con <- make_conover_layer(group = genus.df$diagnosis_group1, df = (family.df$Ruminococcaceae/rowSums(family.df[,6:26])), method = "bh") figS2.c <- ggplot(family.df, aes(x= genus.df$diagnosis_group1 , y = (`Ruminococcaceae`/rowSums(family.df[,6:26], na.rm= TRUE)) , fill = diagnosis_group1 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = loc.con$x, xend = loc.con$xend, y = loc.con$y, yend=loc.con$yend) + annotate("text", x = loc.con$tx, y= loc.con$ty, label = loc.con$sig) + scale_y_continuous() + xlab('Primary Diagnosis') + ylab(expression('Proportion of'~italic('Lachnospiraceae'))) + geom_jitter (aes( colour = diagnosis_group1))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen','darkblue','pink')) + scale_colour_manual(values=c('darkblue','red',"darkorange",'darkgreen','royalblue','purple'))+ theme(legend.position = "none", axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 10, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="c") loc.con <- make_conover_layer(group = family.df$diagnosis_group2, df = (family.df$Lachnospiraceae/rowSums(family.df[,6:26])), method = "bh") figS2.d <- ggplot(family.df, aes(x=diagnosis_group2 , y = (`Lachnospiraceae`/rowSums(family.df[,6:26], na.rm= TRUE)) , fill = diagnosis_group2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = loc.con$x, xend = loc.con$xend, y = loc.con$y, yend=loc.con$yend) + annotate("text", x = loc.con$tx, y= loc.con$ty, label = loc.con$sig) + scale_y_continuous() + xlab('Respiratory Infection') + ylab(expression('Proportion of'~italic('Lachnospiraceae'))) + geom_jitter (aes( colour = diagnosis_group2))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen','goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','orange','green'))+ theme(legend.position = "none", axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 13, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="d") loc.con <- make_conover_layer(group = family.df$infection, df = (family.df$Lachnospiraceae/rowSums(family.df[,6:26])), method = "bh") figS2.e <- ggplot(family.df, aes(x= infection , y = (Lachnospiraceae/rowSums(family.df[,6:26], na.rm= TRUE)) , fill = infection )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = loc.con$x, xend = loc.con$xend, y = loc.con$y, yend=loc.con$yend) + annotate("text", x = loc.con$tx, y= loc.con$ty, label = loc.con$sig) + scale_y_continuous() + xlab('Infection / Non-Infection') + ylab(expression('Proportion of'~italic('Lachnospiraceae'))) + geom_jitter (aes( colour = infection))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen','goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','orange','green'))+ theme(legend.position = "none", axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 13, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="e") figS2 <- grid.arrange(figS2.a, figS2.b , figS2.c, figS2.d, figS2.e, nrow=2) #figS2 ggsave("~/Documents/Kean_2021/Kean_2021_Figure_S2.eps", plot = figS2 ,width = 500,height =283, units = "mm", dpi=300 ) ``` ```{r Figure S3} rb1c <-make_conover_layer(df = genus.df$Alistipes/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.a <- ggplot(genus.df, aes(x= DateRange2 , y = (`Alistipes`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb1c$x, xend = rb1c$xend, y = rb1c$y, yend=rb1c$yend) + annotate("text", x = rb1c$tx, y= rb1c$ty, label = rb1c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Alistipes'))) + geom_jitter (aes( colour = DateRange2))+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen')) + theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title = element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="a") rb3c <-make_conover_layer(df = genus.df$Bacteroides/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.b <- ggplot(genus.df, aes(x= DateRange2 , y = (`Bacteroides`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb3c$x, xend = rb3c$xend, y = rb3c$y, yend=rb3c$yend) + annotate("text", x = rb3c$tx, y= rb3c$ty, label = rb3c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Bacteroides'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title.y = element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="b") rb4c <-make_conover_layer(df = genus.df$Bifidobacterium/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.c <- ggplot(genus.df, aes(x= DateRange2 , y = (`Bifidobacterium`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb4c$x, xend = rb4c$xend, y = rb4c$y, yend=rb4c$yend) + annotate("text", x = rb4c$tx, y= rb4c$ty, label = rb4c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Bifidobacterium'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title.y = element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="c") rb7c <-make_conover_layer(df = genus.df$Coprococcus/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 , method ="bh" ) figS3.d <- ggplot(genus.df, aes(x= DateRange2 , y = (`Coprococcus`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb7c$x, xend = rb7c$xend, y = rb7c$y, yend=rb7c$yend) + annotate("text", x = rb7c$tx, y= rb7c$ty, label = rb7c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Coprococcus'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title.y = element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="d") rb8c <-make_conover_layer(df = genus.df$Desulfovibrio/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.e <- ggplot(genus.df, aes(x= DateRange2 , y = (`Desulfovibrio`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb8c$x, xend = rb8c$xend, y = rb8c$y, yend=rb8c$yend) + annotate("text", x = rb8c$tx, y= rb8c$ty, label = rb8c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Desulfovibrio'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="e") rb11c <-make_conover_layer(df = genus.df$Faecalibacterium/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.f <- ggplot(genus.df, aes(x= DateRange2 , y = (Faecalibacterium/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb11c$x, xend = rb11c$xend, y = rb11c$y, yend=rb11c$yend) + annotate("text", x = rb11c$tx, y= rb11c$ty, label = rb11c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Faecalibacterium'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="f") #g rb14c <-make_conover_layer(df = genus.df$Parabacteroides/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.g <- ggplot(genus.df, aes(x= DateRange2 , y = (`Parabacteroides`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb14c$x, xend = rb14c$xend, y = rb14c$y, yend=rb14c$yend) + annotate("text", x = rb14c$tx, y= rb14c$ty, label = rb14c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Parabacteroides'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="g") rb16c <-make_conover_layer(df = genus.df$Roseburia/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.h <- ggplot(genus.df, aes(x= DateRange2 , y = (`Roseburia`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb16c$x, xend = rb16c$xend, y = rb16c$y, yend=rb16c$yend) + annotate("text", x = rb16c$tx, y= rb16c$ty, label = rb16c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Roseburia'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="h") #h l rb17c <-make_conover_layer(df = (genus.df$Ruminococcus)/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.i <- ggplot(genus.df, aes(x= DateRange2 , y = ((Ruminococcus) /rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb17c$x, xend = rb17c$xend, y = rb17c$y, yend=rb17c$yend) + annotate("text", x = rb17c$tx, y= rb17c$ty, label = rb17c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Ruminococcus'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="o") +labs(tag="i") rb18c <-make_conover_layer(df = genus.df$Subdoligranulum/rowSums(genus.df[,24:182]), group= genus.df$DateRange2 ) figS3.j <- ggplot(genus.df, aes(x= DateRange2 , y = (`Subdoligranulum`/rowSums(genus.df[,24:182], na.rm= TRUE)) , fill = DateRange2 )) + theme_bw() + geom_boxplot( outlier.colour='black', outlier.shape = 'X', notch = TRUE) + annotate("segment", x = rb18c$x, xend = rb18c$xend, y = rb18c$y, yend=rb18c$yend) + annotate("text", x = rb18c$tx, y= rb18c$ty, label = rb18c$sig) + scale_y_continuous() + ylab(expression('Proportion of '~italic('Subdoligranulum'))) + geom_jitter (aes( colour = DateRange2), width = 0.2)+ scale_fill_manual(values=c('lightblue','firebrick', 'goldenrod2','forestgreen')) + scale_colour_manual(values=c('darkblue','red','darkorange','darkgreen'))+ theme(legend.position = "none",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 90, size = 15, hjust = 0.5) , axis.title= element_text(size = 15), axis.text.x.bottom = element_text( size = 15, hjust = 0.5), plot.tag = element_text(size = 15)) +labs(tag="j") figS3 <- grid.arrange(figS3.a, figS3.b, figS3.c, figS3.d, figS3.e, figS3.f, figS3.g, figS3.h, figS3.i, figS3.j, nrow = 3) ggsave("~/Documents/Kean_2021/Kean_2021_Figure_S3.eps", plot = figS3, width = 450, height = 250, units = "mm", dpi = 300) ``` ```{r Figure S4} both.df <- subset(ghici_full_3.df, (ghici_full_3.df$Cholic_acid >0)) both.df <- subset(both.df, both.df$Bacteroides >0 ) both.df$tLCA <- both.df$Lithocholic_acid+both.df$Isolithocholic_Acid both_pat.df <- subset(both.df, both.df$Patient_0no1yes ==1) # list of genera significantly correlated to major primary or secondary bile acids d gen_list <- c("Actinomyces" , "Agathobacter" , "Anaerovorax" , "Barnesiella" , "Collinsella" , "Coprococcus" , "Dorea" , "Eubacterium.hallii.group" , "Eubacterium.oxidoreducens.group", "Faecalitalea" , "Gordonibacter" , "Haemophilus" , "Incertae_sedis" , "Klebsiella" , "Lachnoclostridium" , "Odoribacter" , "Paraprevotella" , "Parasutterella" , "Pseudoflavonifractor" , "Romboutsia" , "Solobacterium" , "Sutterella" , "Turicibacter" ) # list as above with corrected taxonomy gen_list2 <- c("Actinomyces", "Agathobacter", "Anaerobutrycum hallii group", "Anaerovorax", "Barnesiella", "Collinsella", "Coprococcus", "Dorea", "Eubacterium oxidoreducens group", "Faecalitalea" , "Gordonibacter" , "Haemophilus", "Klebsiella", "Lachnoclostridium", "Odoribacter", "Paraprevotella", "Parasutterella", "Pseudoflavonifractor", "Romboutsia", "Solobacterium", "Sutterella" , "Turicibacter" ,"Incertae sedis") tableS3d.df <- data.frame(Genus = character(), BA = character(), rho = numeric(), p_val = numeric(), symbol = character() ) for (i in c("Deoxycholic_Acid","Chenodeoxycholic_Acid","Cholic_acid", "tLCA") ) { for (j in gen_list) { if (colSums(both_pat.df[j]) > 0 ){ spearcor <- cor.test(x =((both_pat.df[,j])/rowSums(both_pat.df[,57:215])), y = ((both_pat.df[,i])/rowSums(both_pat.df[,14:32])), method = "spearman", exact = F)} print(spearcor) if (class(spearcor) != "try-error"){ if (spearcor$p.value >0.05 ){ sp <- "" } else if ((spearcor$p.value <=0.05 ) && (spearcor$p.value >0.01 )){ sp <- "*" } else if ((spearcor$p.value <=0.01 ) && (spearcor$p.value >0.001 )){ sp <- "**" } else if (spearcor$p.value <=0.001 ){ sp <- "***" } else if (is.na(spearcor$p.value) ){ sp = "NA" }} else { sp = "NA" } tableS3d.df %>% add_row( Genus = j, BA =i , p_val = spearcor$p.value, rho =spearcor$estimate , symbol = sp) -> tableS3d.df }} tableS3d.df$Genus <- ifelse(grepl(tableS3d.df$Genus, pattern = "hallii"), "Anaerobutrycum hallii group", tableS3d.df$Genus) tableS3d.df$Genus <- ifelse(grepl(tableS3d.df$Genus, pattern = "sedis"), "Incertae sedis", tableS3d.df$Genus) tableS3d.df$Genus <- ifelse(grepl(tableS3d.df$Genus, pattern = "oxidoreducens"), "Eubacterium oxidoreducens group", tableS3d.df$Genus) tableS3d.df$BA <- ifelse(grepl(tableS3d.df$BA, pattern = "Cheno"), "CDCA", tableS3d.df$BA) tableS3d.df$BA <- ifelse(grepl(tableS3d.df$BA, pattern = "Deoxy"), "DCA", tableS3d.df$BA) tableS3d.df$BA <- ifelse(grepl(tableS3d.df$BA, pattern = "Cholic"), "CA", tableS3d.df$BA) tableS3d.df$BA <- factor(tableS3d.df$BA, levels = c("CA","CDCA","DCA", "tLCA")) tableS3d.df$Genus <- factor(tableS3d.df$Genus, levels = gen_list2) figS4 <- ggplot(data = tableS3d.df, mapping = aes( y = reorder(Genus, desc(Genus)), x = BA, fill = rho)) + geom_tile() + theme_bw()+ scale_fill_gradient2(low = "#053061", mid = "#F7F7F7", high ="#67001F" , breaks=c(-1, -0.8, -0.6, -0.4, -0.2, 0 , 0.2, 0.4, 0.6, 0.8, 1)) + annotate("text", x = tableS3d.df$BA, y = tableS3d.df$Genus, label = tableS3d.df$symbol, hjust = 0.5, vjust = 0.7) + theme(legend.position = "bottom",axis.title.x=element_blank(), axis.text.y.left = element_text(angle = 0, size = 15, hjust = 1, face = "italic") , axis.title= element_text(size = 15), axis.text.x.top = element_text( size = 12, hjust = 0.5), plot.tag = element_text(size = 15), legend.key.width = unit(0.8, units = "cm")) + labs( fill = expression(rho~'[15]'), y = 'Genus') + scale_x_discrete(position = "top") figS4 ggsave("~/Documents/Kean_2021/Kean_2021_Figure_S4.eps", plot = figS4, width = 150, height = 200, units = "mm", dpi = 300 ) ``` ```{r Figure S5} #Set up dataframe for lachnospiraceae identified in genus.df genus.df$group_patient lachno.df <- genus.df[,c(1,4)] lachno.df$Agathobacter <- genus.df$Agathobacter lachno.df$Anaerobutyricum.hallii.group <- genus.df$Eubacterium.hallii.group lachno.df$Anaerocolumna <- genus.df$Anaerocolumna lachno.df$Anaerostignum <- genus.df$Anaerostignum lachno.df$Anaerostipes <- genus.df$Anaerostipes lachno.df$Blautia <- genus.df$Blautia lachno.df$Butyrivibrio <- genus.df$Butyrivibrio lachno.df$Coprococcus <- genus.df$Coprococcus lachno.df$Dorea <- genus.df$Dorea lachno.df$Eisenbergiella <- genus.df$Eisenbergiella lachno.df$Fusicatenibacter <- genus.df$Fusicatenibacter genus.df$Howardella -> lachno.df$Howardella lachno.df$Hungatella <- genus.df$Hungatella genus.df$Lachnoanaerobaculum -> lachno.df$Lachnoanaerobaculum lachno.df$Lachnoclostridium <- genus.df$Lachnoclostridium genus.df$Lachnospira -> lachno.df$Lachnospira lachno.df$Mediterranibacter.gnavus.group <- genus.df$Ruminococcus.gnavus.group lachno.df$Mediterranibacter.torques.group <- genus.df$Ruminococcus.torques.group genus.df$Oribacterium -> lachno.df$Oribacterium genus.df$Pseudobutyrivibrio -> lachno.df$Pseudobutyrivibrio genus.df$Roseburia -> lachno.df$Roseburia genus.df$Stomatobaculum -> lachno.df$Stomatobaculum lachno.df$Tyzzerella <- genus.df$Tyzzerella lachno.df$DateRange2 <- genus.df$DateRange2 #Reshape lachno.df for graphing f8b.m <- melt(lachno.df) #Change formatting f8b.m$variable <- as.character(f8b.m$variable) f8b.m$variable <- ifelse(f8b.m$variable=="Anaerobutyricum.hallii.group", "Anaerobutyricum hallii group", f8b.m$variable) f8b.m$variable <- ifelse(f8b.m$variable=="Ruminococcus.gnavus.group", "Mediterraneibacter gnavus group", f8b.m$variable) f8b.m$variable <- ifelse(f8b.m$variable=="Ruminococcus.torques.group", "Mediterraneibacter torques group", f8b.m$variable) figS5 <- ggplot(f8b.m, mappin = aes(x=Sample_num, y = value, fill = variable))+ geom_col() +theme_bw() + ylab("Raw Count")+ xlab("Sample")+theme(legend.text = element_text(face="italic"), axis.text.x = element_text( angle = 300, hjust = 0, face = "bold"))+ facet_grid(~ DateRange2, scales= "free_x", space = "free_x") + scale_fill_manual(name ="Genus", values=c('royalblue','#e31a1c','firebrick' ,'#fdbf6f','#cab2d6' ,'magenta','#ff7f00','#a6cee3' ,'#6a3d9a','#ffff99','#b15928',"pink","pink2",'#b2df8a', '#33a02c','#fb9a99' ,'#1f78b4','#fdbf6f','#ff7f00','#cab2d6','skyblue','#e31a1c', "pink", " purple"))+ guides(fill = guide_legend(ncol = 1)) figS5 ggsave(filename = "~/Documents/Kean_2021/Kean_2021_Figure_S5.eps", plot = figS5, width = 450, height = 250, units = "mm", dpi = 300) ``` ```{r Table S4} d8.df <- subset(genus.df, genus.df$DateRange2 =="d8-10") lachno.list <- list("Agathobacter", "Anaerobutyricum.hallii.group", "Anaerocolumna", "Anaerostignum", "Anaerostipes", "Blautia", "Butyrivibrio", "Coprococcus", "Dorea", "Eisenbergiella", "Fusicatenibacter", "Howardella", "Hungatella", "Lachnoanaerobaculum", "Lachnoclostridium", "Lachnospira", "Mediterraneibacter.gnavus.group", "Mediterraneibacter.torques.group", "Oribacterium", "Pseudobutyrivibrio", "Roseburia", "Stomatobaculum" ,"Tyzzerella") bact.list <- c('A2', 'ASF356', 'Abyssivirga',"Anaerobutyricum", 'Acetatifactor',"Mediterraneibacter", 'Acetitomaculum', 'Agathobacter', 'Anaerobium', 'Anaerocolumna', 'Anaerosporobacter', 'Anaerostignum', 'Anaerostipes', 'Blautia', 'Butyrivibrio', 'CAG-56', 'CHKCI001', 'Catenibacillus', 'Catonella', 'Cellulosilyticum', 'Clostridium', 'Coprococcus', 'Cuneatibacter', 'Defluviitalea', 'Defluviitaleaceae', 'Dorea', 'Eisenbergiella', 'Epulopiscium', 'Eubacterium', 'FD2005', 'Frisingicoccus', 'Fusicatenibacter', 'GCA-900066575', 'GCA-900066755', 'Herbinix', 'Howardella', 'Hungatella', 'Incertae', 'Johnsonella', 'Lachnoanaerobaculum', 'Lachnobacterium', 'Lachnoclostridium', 'Lachnospira', 'Lachnospiraceae', 'Lachnotalea', 'Lactonifactor', 'Marvinbryantia', 'Mobilisporobacter', 'Mobilitalea', 'Moryella', 'Murimonas', 'NK4A214', 'Natranaerovirga', 'Oribacterium', 'Parasporobacterium', 'Pseudobutyrivibrio', 'Robinsoniella', 'Roseburia', 'Ruminococcus', 'Sellimonas', 'Sharpea', 'Shuttleworthia', 'Stomatobaculum', 'Syntrophococcus', 'Tuzzerella', 'Tyzzerella', 'UC5-1-2E3', 'Vallitalea', 'XBB1006', '[Acetivibrio]', '[Bacteroides]', '[Eubacterium]', '[Ruminococcus]', 'possible', 'probable', 'uncultured') bact.list2 <- NULL for (j in colnames(genus.df)){ for (i in lachno.list) { print(i) if (grepl(colnames(.df)[j], pattern = i)){ append(x = bact.list2, values = i) } }} colnames(genus.df) bact.list2 genus.df$Butyricicoccus colnames(d8.df)[49] <- "Anaerobutyricum.hallii.group" colnames(d8.df)[40] <- "Mediterraneibacter.torques.group" colnames(d8.df)[93] <- "Mediterraneibacter.gnavus.group" hallii_conf.df <- data.frame(Lac = character(),Comp = character(),S_cor=double(),S_p_val=double()) for (i in lachno.list){ if (sum(d8.df[,i]) >=10){ for (x in 25:182) { if (median(d8.df[,x]) >=5){ s <- cor.test(d8.df[,colnames(d8.df)[x]]/rowSums(d8.df[24:182]), d8.df[,i]/rowSums(d8.df[24:182]), method = "spearman", exact =F) #print(s) if ( s$p.value <= 0.1 ) { hallii_conf.df %>% add_row(Lac = i, Comp = colnames(d8.df)[x], S_cor = s$estimate, S_p_val=s$p.value) -> hallii_conf.df }}}}} write_delim(x = hallii_conf.df, file = "~/Documents/Kean_2021/Kean_2021_Table_S3.csv", delim = ",") ```