R/get_scatter_plots.R
In kuppal2/xmsPANDA: R Package for Biomarker Discovery, Network, and Data Exploratory Analysis
get_scatter_plots <-
function (X = NA, Y = NA, feature_table_file, parentoutput_dir,
class_labels_file, group_by_mat_file = NA, scatterplot.col.opt = "journal",
alphacol = 0.3, newdevice = TRUE, cex.plots = 0.6, replace.by.NA = FALSE,
pairedanalysis = FALSE, filename = "", ylabel = "Response",
alphabetical.order = FALSE, name = NA, add.jitter = TRUE,
add.pvalues = TRUE, xlabel = "Predictor", ellipse = FALSE,
ypos.adj.factor = 0.5, group_by_mat = NA, cor.method = "pearson", multiple.facets=TRUE,
conf.int=TRUE,
...)
{
suppressMessages(library(ggpubr))
if (is.na(X[1]) == TRUE) {
data_matrix <- read.table(feature_table_file, sep = "\t",
header = TRUE)
}
else {
data_matrix <- X
}
if (is.na(Y[1]) == TRUE) {
classlabels <- read.table(class_labels_file, sep = "\t",
header = TRUE)
}
else {
classlabels <- Y
}
if (is.na(group_by_mat_file[1]) == FALSE) {
group_by_mat <- read.table(group_by_mat_file, sep = "\t",
header = TRUE)
}
class_labels_levels <- c("A")
sample.col.opt = scatterplot.col.opt
if (sample.col.opt == "default") {
col_vec <- c("#CC0000", "#AAC000", "blue",
"mediumpurple4", "mediumpurple1", "blueviolet",
"cornflowerblue", "cyan4", "skyblue",
"darkgreen", "seagreen1", "green",
"yellow", "orange", "pink", "coral1",
"palevioletred2", "red", "saddlebrown",
"brown", "brown3", "white", "darkgray",
"aliceblue", "aquamarine", "aquamarine3",
"bisque", "burlywood1", "lavender",
"khaki3", "black")
}
else {
if (sample.col.opt == "topo") {
col_vec <- topo.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "heat") {
col_vec <- heat.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "rainbow") {
col_vec <- rainbow(length(class_labels_levels),
start = 0, end = alphacol)
}
else {
if (sample.col.opt == "terrain") {
col_vec <- cm.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "colorblind") {
if (length(class_labels_levels) < 9) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9", "#D55E00",
"#CC79A7", "#E64B35FF",
"grey57")
}
else {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9", "#D55E00",
"#CC79A7", "#E64B35B2",
"#4DBBD5B2", "#00A087B2",
"#3C5488B2", "#F39B7FB2",
"#8491B4B2", "#91D1C2B2",
"#DC0000B2", "#7E6148B2",
"#374E55B2", "#DF8F44B2",
"#00A1D5B2", "#B24745B2",
"#79AF97B2", "#6A6599B2",
"#80796BB2", "#0073C2B2",
"#EFC000B2", "#868686B2",
"#CD534CB2", "#7AA6DCB2",
"#003C67B2", "grey57")
}
}
else {
check_brewer <- grep(pattern = "brewer",
x = sample.col.opt)
if (length(check_brewer) > 0) {
sample.col.opt_temp = gsub(x = sample.col.opt,
pattern = "brewer.", replacement = "")
col_vec <- colorRampPalette(brewer.pal(10,
sample.col.opt_temp))(length(class_labels_levels))
}
else {
if (sample.col.opt == "journal") {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"#E64B35FF", "#3C5488FF",
"#F39B7FFF", "#8491B4FF",
"#91D1C2FF", "#DC0000FF",
"#B09C85FF", "#5F559BFF",
"#808180FF", "#20854EFF",
"#FFDC91FF", "#B24745FF",
"#374E55FF", "#8F7700FF",
"#5050FFFF", "#6BD76BFF",
"#E64B3519", "#4DBBD519",
"#631879E5", "grey75")
if (length(class_labels_levels) < 8) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"grey75")
}
else {
if (length(class_labels_levels) <=
28) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"#E64B35FF", "#3C5488FF",
"#F39B7FFF", "#8491B4FF",
"#91D1C2FF", "#DC0000FF",
"#B09C85FF", "#5F559BFF",
"#808180FF", "#20854EFF",
"#FFDC91FF", "#B24745FF",
"#374E55FF", "#8F7700FF",
"#5050FFFF", "#6BD76BFF",
"#8BD76BFF", "#E64B3519",
"#9DBBD0FF", "#631879E5",
"#666666", "grey75")
}
else {
colfunc <- colorRampPalette(c("#0072B2",
"#E69F00", "#009E73",
"#56B4E9", "#D55E00",
"#CC79A7", "grey75"))
col_vec <- colfunc(length(class_labels_levels))
col_vec <- col_vec[sample(col_vec)]
}
}
}
else {
# if (length(sample.col.opt) == 1) {
# col_vec <- rep(sample.col.opt, length(class_labels_levels))
#}
#else {
# colfunc <- colorRampPalette(sample.col.opt)
# col_vec <- colfunc(length(class_labels_levels))
#}
if(length(sample.col.opt)==1){
col_vec <-rep(sample.col.opt,length(class_labels_levels))
}else{
if(length(sample.col.opt)>=length(class_labels_levels)){
col_vec <-sample.col.opt
col_vec <- rep(col_vec,length(class_labels_levels))
}else{
colfunc <-colorRampPalette(sample.col.opt);col_vec<-colfunc(length(class_labels_levels))
}
}
}
}
}
}
}
}
}
}
cnames <- colnames(data_matrix)
cnames <- tolower(cnames)
cnames <- tolower(cnames)
check_names <- grep(cnames, pattern = "^name$")
if (length(check_names) > 0) {
if (check_names == 1) {
check_names1 <- grep(cnames, pattern = "^mz$")
check_names2 <- grep(cnames, pattern = "^time$")
if (length(check_names1) < 1 & length(check_names2) <
1) {
mz <- seq(1.00001, nrow(data_matrix) + 1, 1)
time <- seq(1.01, nrow(data_matrix) + 1, 1)
check_ind <- gregexpr(cnames, pattern = "^name$")
check_ind <- which(check_ind > 0)
X <- as.data.frame(data_matrix)
Name <- as.character(X[, check_ind])
X <- cbind(mz, time, X[, -check_ind])
names_with_mz_time = cbind(Name, mz, time)
names_with_mz_time <- as.data.frame(names_with_mz_time)
write.table(names_with_mz_time, file = "Stage1/Name_mz_time_mapping.txt",
sep = "\t", row.names = FALSE)
X <- as.data.frame(X)
}
else {
if (length(check_names1) > 0 & length(check_names2) >
0) {
check_ind <- gregexpr(cnames, pattern = "^name$")
check_ind <- which(check_ind > 0)
Name <- as.character(X[, check_ind])
X <- X[, -check_ind]
names_with_mz_time = cbind(Name, X$mz, X$time)
colnames(names_with_mz_time) <- c("Name",
"mz", "time")
names_with_mz_time <- as.data.frame(names_with_mz_time)
X <- as.data.frame(X)
write.table(names_with_mz_time, file = "Stage1/Name_mz_time_mapping.txt",
sep = "\t", row.names = FALSE)
}
}
}
}
else {
check_names1 <- grep(cnames[1], pattern = "^mz$")
check_names2 <- grep(cnames[2], pattern = "^time$")
if (length(check_names1) < 1 || length(check_names2) <
1) {
stop("Invalid feature table format. The format should be either Name in column A or mz and time in columns A and B. Please check example files.")
}
}
dir.create(parentoutput_dir,showWarnings = FALSE)
setwd(parentoutput_dir)
data_matrix <- X
data_m <- data_matrix[, -c(1:2)]
data_m <- as.matrix(data_m)
mzvec <- data_matrix[, 1]
timevec <- data_matrix[, 2]
goodfeats <- data_m
rm(data_m)
rm(X)
rm(Y)
file_ind <- 0
boxplots_fname <- paste("scatterplots", filename, ".pdf",
sep = "")
if (newdevice == TRUE) {
pdf(boxplots_fname)
}
par(mfrow = c(1, 1), family = "sans", cex = cex.plots)
class_vec <- classlabels[, 2]
lapply(1:dim(goodfeats)[1], function(m) {
if (m%%9 == 0) {
file_ind <- file_ind + 1
boxplots_fname <- paste("scatterplots_file",
file_ind, ".tiff", sep = "")
}
# round_mzval <- sprintf("%.4f", mzvec[m])
#round_timeval <- sprintf("%.1f", timevec[m])
if (is.na(name) == TRUE) {
if (length(check_names) > 0) {
if (check_names == 1) {
mzname <- as.character(names_with_mz_time[m, 1])
}
else {
mzname <- paste("mz_time: ", round_mzval,
"_", round_timeval, sep = "")
}
}
else {
mzname <- paste("mz_time: ", round_mzval,
"_", round_timeval, sep = "")
}
}
else {
mzname = as.character(name[m])
}
cur_d <- new("list")
feat_vec <- {
}
temp_dm <- cbind(colnames(goodfeats), class_vec, as.vector(t(goodfeats[m,
])))
temp_dm <- as.data.frame(temp_dm)
colnames(temp_dm) <- c("SID", "Class", "Feature")
temp_dm$Class <- as.numeric(as.character(temp_dm$Class))
temp_dm$Feature <- as.numeric(as.character(temp_dm$Feature))
par(mfrow = c(1, 1), family = "sans", cex = cex.plots)
w <- 0.1
par(omd = c(0, 1 - w, 0, 1), cex.main = 0.7)
if (is.na(group_by_mat[1]) == FALSE) {
colnames(group_by_mat) <- c("SID", "GroupBy")
temp_dm <- merge(temp_dm, group_by_mat, by = "SID")
}
temp_dm <- as.data.frame(temp_dm)
s1 = summary(temp_dm$Feature)
sadj = (s1[5] - s1[3]) * ypos.adj.factor
if (is.na(group_by_mat[1]) == TRUE) {
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
palette = col_vec[1], col = col_vec[1], shape = 20,
size = 3, add = "reg.line",
add.params = list(color = "black",
fill = "lightgray"))) + theme(plot.title = element_text(hjust = 0.5, size = 10)) + stat_cor(method = cor.method,
label.y = max(temp_dm$Feature + (sadj)))
}
else {
temp_dm$GroupBy <- as.factor(temp_dm$GroupBy)
if(multiple.facets==TRUE){
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
add = "reg.line", color = "GroupBy", facet.by="GroupBy", scales="free",
palette = col_vec, fullrange = TRUE, shapez = 20,
size = 3)) + theme(plot.title = element_text(hjust = 0.5,
size = 10)) + stat_cor(method = cor.method, aes(color = GroupBy))
}else{
#ylim=c(s1[1],s1[6]),
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
add = "reg.line", color = "GroupBy",
palette = col_vec, fullrange = TRUE, shape = 20,
size = 3)) + theme(plot.title = element_text(hjust = 0.5,
size = 10)) + stat_cor(method = cor.method, aes(color = GroupBy))
}
}
suppressMessages(print(p))
})
if (newdevice == TRUE) {
dev.off()
}
}
kuppal2/xmsPANDA documentation built on May 15, 2021, 5:48 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
get_scatter_plots <-
function (X = NA, Y = NA, feature_table_file, parentoutput_dir,
class_labels_file, group_by_mat_file = NA, scatterplot.col.opt = "journal",
alphacol = 0.3, newdevice = TRUE, cex.plots = 0.6, replace.by.NA = FALSE,
pairedanalysis = FALSE, filename = "", ylabel = "Response",
alphabetical.order = FALSE, name = NA, add.jitter = TRUE,
add.pvalues = TRUE, xlabel = "Predictor", ellipse = FALSE,
ypos.adj.factor = 0.5, group_by_mat = NA, cor.method = "pearson", multiple.facets=TRUE,
conf.int=TRUE,
...)
{
suppressMessages(library(ggpubr))
if (is.na(X[1]) == TRUE) {
data_matrix <- read.table(feature_table_file, sep = "\t",
header = TRUE)
}
else {
data_matrix <- X
}
if (is.na(Y[1]) == TRUE) {
classlabels <- read.table(class_labels_file, sep = "\t",
header = TRUE)
}
else {
classlabels <- Y
}
if (is.na(group_by_mat_file[1]) == FALSE) {
group_by_mat <- read.table(group_by_mat_file, sep = "\t",
header = TRUE)
}
class_labels_levels <- c("A")
sample.col.opt = scatterplot.col.opt
if (sample.col.opt == "default") {
col_vec <- c("#CC0000", "#AAC000", "blue",
"mediumpurple4", "mediumpurple1", "blueviolet",
"cornflowerblue", "cyan4", "skyblue",
"darkgreen", "seagreen1", "green",
"yellow", "orange", "pink", "coral1",
"palevioletred2", "red", "saddlebrown",
"brown", "brown3", "white", "darkgray",
"aliceblue", "aquamarine", "aquamarine3",
"bisque", "burlywood1", "lavender",
"khaki3", "black")
}
else {
if (sample.col.opt == "topo") {
col_vec <- topo.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "heat") {
col_vec <- heat.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "rainbow") {
col_vec <- rainbow(length(class_labels_levels),
start = 0, end = alphacol)
}
else {
if (sample.col.opt == "terrain") {
col_vec <- cm.colors(length(class_labels_levels),
alpha = alphacol)
}
else {
if (sample.col.opt == "colorblind") {
if (length(class_labels_levels) < 9) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9", "#D55E00",
"#CC79A7", "#E64B35FF",
"grey57")
}
else {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9", "#D55E00",
"#CC79A7", "#E64B35B2",
"#4DBBD5B2", "#00A087B2",
"#3C5488B2", "#F39B7FB2",
"#8491B4B2", "#91D1C2B2",
"#DC0000B2", "#7E6148B2",
"#374E55B2", "#DF8F44B2",
"#00A1D5B2", "#B24745B2",
"#79AF97B2", "#6A6599B2",
"#80796BB2", "#0073C2B2",
"#EFC000B2", "#868686B2",
"#CD534CB2", "#7AA6DCB2",
"#003C67B2", "grey57")
}
}
else {
check_brewer <- grep(pattern = "brewer",
x = sample.col.opt)
if (length(check_brewer) > 0) {
sample.col.opt_temp = gsub(x = sample.col.opt,
pattern = "brewer.", replacement = "")
col_vec <- colorRampPalette(brewer.pal(10,
sample.col.opt_temp))(length(class_labels_levels))
}
else {
if (sample.col.opt == "journal") {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"#E64B35FF", "#3C5488FF",
"#F39B7FFF", "#8491B4FF",
"#91D1C2FF", "#DC0000FF",
"#B09C85FF", "#5F559BFF",
"#808180FF", "#20854EFF",
"#FFDC91FF", "#B24745FF",
"#374E55FF", "#8F7700FF",
"#5050FFFF", "#6BD76BFF",
"#E64B3519", "#4DBBD519",
"#631879E5", "grey75")
if (length(class_labels_levels) < 8) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"grey75")
}
else {
if (length(class_labels_levels) <=
28) {
col_vec <- c("#0072B2", "#E69F00",
"#009E73", "#56B4E9",
"#D55E00", "#CC79A7",
"#E64B35FF", "#3C5488FF",
"#F39B7FFF", "#8491B4FF",
"#91D1C2FF", "#DC0000FF",
"#B09C85FF", "#5F559BFF",
"#808180FF", "#20854EFF",
"#FFDC91FF", "#B24745FF",
"#374E55FF", "#8F7700FF",
"#5050FFFF", "#6BD76BFF",
"#8BD76BFF", "#E64B3519",
"#9DBBD0FF", "#631879E5",
"#666666", "grey75")
}
else {
colfunc <- colorRampPalette(c("#0072B2",
"#E69F00", "#009E73",
"#56B4E9", "#D55E00",
"#CC79A7", "grey75"))
col_vec <- colfunc(length(class_labels_levels))
col_vec <- col_vec[sample(col_vec)]
}
}
}
else {
# if (length(sample.col.opt) == 1) {
# col_vec <- rep(sample.col.opt, length(class_labels_levels))
#}
#else {
# colfunc <- colorRampPalette(sample.col.opt)
# col_vec <- colfunc(length(class_labels_levels))
#}
if(length(sample.col.opt)==1){
col_vec <-rep(sample.col.opt,length(class_labels_levels))
}else{
if(length(sample.col.opt)>=length(class_labels_levels)){
col_vec <-sample.col.opt
col_vec <- rep(col_vec,length(class_labels_levels))
}else{
colfunc <-colorRampPalette(sample.col.opt);col_vec<-colfunc(length(class_labels_levels))
}
}
}
}
}
}
}
}
}
}
cnames <- colnames(data_matrix)
cnames <- tolower(cnames)
cnames <- tolower(cnames)
check_names <- grep(cnames, pattern = "^name$")
if (length(check_names) > 0) {
if (check_names == 1) {
check_names1 <- grep(cnames, pattern = "^mz$")
check_names2 <- grep(cnames, pattern = "^time$")
if (length(check_names1) < 1 & length(check_names2) <
1) {
mz <- seq(1.00001, nrow(data_matrix) + 1, 1)
time <- seq(1.01, nrow(data_matrix) + 1, 1)
check_ind <- gregexpr(cnames, pattern = "^name$")
check_ind <- which(check_ind > 0)
X <- as.data.frame(data_matrix)
Name <- as.character(X[, check_ind])
X <- cbind(mz, time, X[, -check_ind])
names_with_mz_time = cbind(Name, mz, time)
names_with_mz_time <- as.data.frame(names_with_mz_time)
write.table(names_with_mz_time, file = "Stage1/Name_mz_time_mapping.txt",
sep = "\t", row.names = FALSE)
X <- as.data.frame(X)
}
else {
if (length(check_names1) > 0 & length(check_names2) >
0) {
check_ind <- gregexpr(cnames, pattern = "^name$")
check_ind <- which(check_ind > 0)
Name <- as.character(X[, check_ind])
X <- X[, -check_ind]
names_with_mz_time = cbind(Name, X$mz, X$time)
colnames(names_with_mz_time) <- c("Name",
"mz", "time")
names_with_mz_time <- as.data.frame(names_with_mz_time)
X <- as.data.frame(X)
write.table(names_with_mz_time, file = "Stage1/Name_mz_time_mapping.txt",
sep = "\t", row.names = FALSE)
}
}
}
}
else {
check_names1 <- grep(cnames[1], pattern = "^mz$")
check_names2 <- grep(cnames[2], pattern = "^time$")
if (length(check_names1) < 1 || length(check_names2) <
1) {
stop("Invalid feature table format. The format should be either Name in column A or mz and time in columns A and B. Please check example files.")
}
}
dir.create(parentoutput_dir,showWarnings = FALSE)
setwd(parentoutput_dir)
data_matrix <- X
data_m <- data_matrix[, -c(1:2)]
data_m <- as.matrix(data_m)
mzvec <- data_matrix[, 1]
timevec <- data_matrix[, 2]
goodfeats <- data_m
rm(data_m)
rm(X)
rm(Y)
file_ind <- 0
boxplots_fname <- paste("scatterplots", filename, ".pdf",
sep = "")
if (newdevice == TRUE) {
pdf(boxplots_fname)
}
par(mfrow = c(1, 1), family = "sans", cex = cex.plots)
class_vec <- classlabels[, 2]
lapply(1:dim(goodfeats)[1], function(m) {
if (m%%9 == 0) {
file_ind <- file_ind + 1
boxplots_fname <- paste("scatterplots_file",
file_ind, ".tiff", sep = "")
}
# round_mzval <- sprintf("%.4f", mzvec[m])
#round_timeval <- sprintf("%.1f", timevec[m])
if (is.na(name) == TRUE) {
if (length(check_names) > 0) {
if (check_names == 1) {
mzname <- as.character(names_with_mz_time[m, 1])
}
else {
mzname <- paste("mz_time: ", round_mzval,
"_", round_timeval, sep = "")
}
}
else {
mzname <- paste("mz_time: ", round_mzval,
"_", round_timeval, sep = "")
}
}
else {
mzname = as.character(name[m])
}
cur_d <- new("list")
feat_vec <- {
}
temp_dm <- cbind(colnames(goodfeats), class_vec, as.vector(t(goodfeats[m,
])))
temp_dm <- as.data.frame(temp_dm)
colnames(temp_dm) <- c("SID", "Class", "Feature")
temp_dm$Class <- as.numeric(as.character(temp_dm$Class))
temp_dm$Feature <- as.numeric(as.character(temp_dm$Feature))
par(mfrow = c(1, 1), family = "sans", cex = cex.plots)
w <- 0.1
par(omd = c(0, 1 - w, 0, 1), cex.main = 0.7)
if (is.na(group_by_mat[1]) == FALSE) {
colnames(group_by_mat) <- c("SID", "GroupBy")
temp_dm <- merge(temp_dm, group_by_mat, by = "SID")
}
temp_dm <- as.data.frame(temp_dm)
s1 = summary(temp_dm$Feature)
sadj = (s1[5] - s1[3]) * ypos.adj.factor
if (is.na(group_by_mat[1]) == TRUE) {
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
palette = col_vec[1], col = col_vec[1], shape = 20,
size = 3, add = "reg.line",
add.params = list(color = "black",
fill = "lightgray"))) + theme(plot.title = element_text(hjust = 0.5, size = 10)) + stat_cor(method = cor.method,
label.y = max(temp_dm$Feature + (sadj)))
}
else {
temp_dm$GroupBy <- as.factor(temp_dm$GroupBy)
if(multiple.facets==TRUE){
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
add = "reg.line", color = "GroupBy", facet.by="GroupBy", scales="free",
palette = col_vec, fullrange = TRUE, shapez = 20,
size = 3)) + theme(plot.title = element_text(hjust = 0.5,
size = 10)) + stat_cor(method = cor.method, aes(color = GroupBy))
}else{
#ylim=c(s1[1],s1[6]),
p <- suppressMessages(ggscatter(temp_dm, y = "Class", x = "Feature", conf.int=conf.int,
title = mzname, xlab = xlabel, ylab = ylabel,
add = "reg.line", color = "GroupBy",
palette = col_vec, fullrange = TRUE, shape = 20,
size = 3)) + theme(plot.title = element_text(hjust = 0.5,
size = 10)) + stat_cor(method = cor.method, aes(color = GroupBy))
}
}
suppressMessages(print(p))
})
if (newdevice == TRUE) {
dev.off()
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.