R/Plot_PCA.R
In AbhishekSinha28/tcgaCleaneR: TGCA Data Analysis
Defines functions
plotPC
Documented in
plotPC
# Plot PCA function
#' @title PCA Visualization
#'
#' @description This function is a part of the data analysis functionality of `tcgaCleaneR`. It helps to visualize the PCs from \code{get.pca}.
#'
#' @param pca.data list: PCA output from \code{computePCA}.
#' @param data S4 data object
#' @param group character: Color code PCs based on group. groups included are 'Time', 'Tissue', 'Plate', 'TSS', 'Center'
#' @param plot_type character: Plot type
#' @param pcs.no numeric vector: PCs that needs to be plotted
#'
#' @return Density Plot, Box Plot
#' @export
#'
#' @importFrom ggplot2 ggplot
#' @importFrom ggplot2 aes
#' @importFrom ggplot2 xlab
#' @importFrom ggplot2 ylab
#' @importFrom ggplot2 geom_point
#' @importFrom ggplot2 scale_x_continuous
#' @importFrom ggplot2 scale_y_continuous
#' @importFrom ggplot2 theme
#' @importFrom ggplot2 element_blank
#' @importFrom ggplot2 element_line
#' @importFrom ggplot2 element_text
#' @importFrom ggplot2 scale_fill_manual
#' @importFrom ggplot2 geom_density
#' @importFrom ggplot2 coord_flip
#' @importFrom ggplot2 geom_line
#' @importFrom ggplot2 scale_color_manual
#' @importFrom ggplot2 ggtitle
#' @importFrom ggplot2 guides
#' @importFrom ggplot2 guide_legend
#' @importFrom cowplot axis_canvas
#' @importFrom cowplot insert_xaxis_grob
#' @importFrom cowplot insert_yaxis_grob
#'
#' @examples
#' \dontrun{
#' plotPC(pca.data, data = brca.data, group = "Time", plot_type = "DensityPlot", pcs.no = c(1,2,3))
#' plotPC(pca.data = df6, data = brca.data, group = "Plate", plot_type = "BoxPlot", pcs.no = c(1,2,4))
#' }
plotPC <- function(pca.data, data, group, plot_type, pcs.no){
.scatter.density.pc <- function(
pcs,
pc.var,
pcs.no,
group.name,
group,
color,
strokeSize,
pointSize,
strokeColor,
alpha){
colnames(pcs) <- paste0('pc', pcs.no)
pair.pcs <- utils::combn(ncol(pcs), 2)
pcs.var <- utils::combn(pcs.no, 2)
pList <- list()
for(i in 1:ncol(pair.pcs)){
if(i == 1){
x <- pair.pcs[1,i]
y <- pair.pcs[2,i]
a <- pcs.var[1,i]
b <- pcs.var[2,i]
p <- ggplot(mapping = aes(
x = pcs[,x],
y = pcs[,y],
fill = group)) +
xlab(paste0('PC', a, ' (', pc.var[a], '%)')) +
ylab(paste0('PC', b, ' (', pc.var[b], '%)')) +
geom_point(
aes(fill = group),
pch = 21,
color = strokeColor,
stroke = strokeSize,
size = pointSize,
alpha = alpha) +
scale_x_continuous(breaks = scales::pretty_breaks(n = 5)) +
scale_y_continuous(breaks = scales::pretty_breaks(n = 5)) +
theme(
legend.position = "right",
panel.background = element_blank(),
axis.line = element_line(colour = "black", size = 1.1),
legend.background = element_blank(),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
legend.key = element_blank(),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
axis.title.x = element_text(size = 14),
axis.title.y = element_text(size = 14)) +
guides(fill = guide_legend(override.aes = list(size = 4))) +
scale_fill_manual(name = group.name, values = color)
le <- ggpubr::get_legend(p)
}else{
x <- pair.pcs[1,i]
y <- pair.pcs[2,i]
a <- pcs.var[1,i]
b <- pcs.var[2,i]
p <- ggplot(mapping = aes(
x = pcs[,x],
y = pcs[,y],
fill = group)) +
xlab(paste0('PC', a, ' (',pc.var[a], '%)')) +
ylab(paste0('PC', b, ' (',pc.var[b], '%)')) +
geom_point(
aes(fill = group),
pch = 21,
color = strokeColor,
stroke = strokeSize,
size = pointSize,
alpha = alpha) +
scale_x_continuous(breaks = scales::pretty_breaks(n = 5)) +
scale_y_continuous(breaks = scales::pretty_breaks(n = 5)) +
theme(
panel.background = element_blank(),
axis.line = element_line(colour = "black", size = 1.1),
legend.position = "none",
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
axis.title.x = element_text(size = 14),
axis.title.y = element_text(size = 14)) +
scale_fill_manual(values = color, name = group.name)
}
p <- p + ggplot2::theme(legend.position = "none")
xdens <- cowplot::axis_canvas(p, axis = "x")+
ggplot2::geom_density(
mapping = ggplot2::aes(
x = pcs[,x],
fill = group),
alpha = 0.7,
size = 0.2
) +
ggplot2::theme(legend.position = "none") +
ggplot2::scale_fill_manual(values = color)
ydens <- cowplot::axis_canvas(
p,
axis = "y",
coord_flip = TRUE) +
ggplot2::geom_density(
mapping = ggplot2::aes(
x = pcs[,y],
fill = group),
alpha = 0.7,
size = 0.2) +
ggplot2::theme(legend.position = "none") +
ggplot2::scale_fill_manual(name = group.name, values = color) +
ggplot2::coord_flip()
p1 <- insert_xaxis_grob(
p,
xdens,
grid::unit(.2, "null"),
position = "top"
)
p2 <- insert_yaxis_grob(
p1,
ydens,
grid::unit(.2, "null"),
position = "right"
)
pList[[i]] <- ggdraw(p2)
}
pList[[i+1]] <- le
return(pList)
}
sample.info <- as.data.frame(SummarizedExperiment::colData(data))
data.set.names <- names(SummarizedExperiment::assays(data))
if (group == "Time"){
if(plot_type == "DensityPlot"){
currentCols <- RColorBrewer::brewer.pal(8, "Dark2")[-5]
years.colors <- currentCols[1:length(unique(sample.info$Year))]
pca.plots.time <- lapply(
data.set.names,#tcga.harmonized,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Time',
group = sample.info$Year,
color = years.colors,#unique(sample.info$Year),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4, top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Year
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
}
else
if (group == "Tissue"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Tissue',
group = sample.info$Tissues,
color = c("#252525","#D9D9D9"),#c('red', 'blue'),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Tissues
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "Plate"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Plate',
group = sample.info$Plates,
color = unique(factor(sample.info$Plates)),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Plates
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "TSS"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'TSS',
group = sample.info$TSS,
color = unique(factor(sample.info$TSS)),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$TSS
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "Center"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Center',
group = sample.info$Center,
color = unique(sample.info$Center),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Center
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
}
#return(data.set.names)
}
AbhishekSinha28/tcgaCleaneR documentation built on May 6, 2022, 6:46 a.m.
R Package Documentation
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Defines functions plotPC
Documented in plotPC
# Plot PCA function
#' @title PCA Visualization
#'
#' @description This function is a part of the data analysis functionality of `tcgaCleaneR`. It helps to visualize the PCs from \code{get.pca}.
#'
#' @param pca.data list: PCA output from \code{computePCA}.
#' @param data S4 data object
#' @param group character: Color code PCs based on group. groups included are 'Time', 'Tissue', 'Plate', 'TSS', 'Center'
#' @param plot_type character: Plot type
#' @param pcs.no numeric vector: PCs that needs to be plotted
#'
#' @return Density Plot, Box Plot
#' @export
#'
#' @importFrom ggplot2 ggplot
#' @importFrom ggplot2 aes
#' @importFrom ggplot2 xlab
#' @importFrom ggplot2 ylab
#' @importFrom ggplot2 geom_point
#' @importFrom ggplot2 scale_x_continuous
#' @importFrom ggplot2 scale_y_continuous
#' @importFrom ggplot2 theme
#' @importFrom ggplot2 element_blank
#' @importFrom ggplot2 element_line
#' @importFrom ggplot2 element_text
#' @importFrom ggplot2 scale_fill_manual
#' @importFrom ggplot2 geom_density
#' @importFrom ggplot2 coord_flip
#' @importFrom ggplot2 geom_line
#' @importFrom ggplot2 scale_color_manual
#' @importFrom ggplot2 ggtitle
#' @importFrom ggplot2 guides
#' @importFrom ggplot2 guide_legend
#' @importFrom cowplot axis_canvas
#' @importFrom cowplot insert_xaxis_grob
#' @importFrom cowplot insert_yaxis_grob
#'
#' @examples
#' \dontrun{
#' plotPC(pca.data, data = brca.data, group = "Time", plot_type = "DensityPlot", pcs.no = c(1,2,3))
#' plotPC(pca.data = df6, data = brca.data, group = "Plate", plot_type = "BoxPlot", pcs.no = c(1,2,4))
#' }
plotPC <- function(pca.data, data, group, plot_type, pcs.no){
.scatter.density.pc <- function(
pcs,
pc.var,
pcs.no,
group.name,
group,
color,
strokeSize,
pointSize,
strokeColor,
alpha){
colnames(pcs) <- paste0('pc', pcs.no)
pair.pcs <- utils::combn(ncol(pcs), 2)
pcs.var <- utils::combn(pcs.no, 2)
pList <- list()
for(i in 1:ncol(pair.pcs)){
if(i == 1){
x <- pair.pcs[1,i]
y <- pair.pcs[2,i]
a <- pcs.var[1,i]
b <- pcs.var[2,i]
p <- ggplot(mapping = aes(
x = pcs[,x],
y = pcs[,y],
fill = group)) +
xlab(paste0('PC', a, ' (', pc.var[a], '%)')) +
ylab(paste0('PC', b, ' (', pc.var[b], '%)')) +
geom_point(
aes(fill = group),
pch = 21,
color = strokeColor,
stroke = strokeSize,
size = pointSize,
alpha = alpha) +
scale_x_continuous(breaks = scales::pretty_breaks(n = 5)) +
scale_y_continuous(breaks = scales::pretty_breaks(n = 5)) +
theme(
legend.position = "right",
panel.background = element_blank(),
axis.line = element_line(colour = "black", size = 1.1),
legend.background = element_blank(),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
legend.key = element_blank(),
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
axis.title.x = element_text(size = 14),
axis.title.y = element_text(size = 14)) +
guides(fill = guide_legend(override.aes = list(size = 4))) +
scale_fill_manual(name = group.name, values = color)
le <- ggpubr::get_legend(p)
}else{
x <- pair.pcs[1,i]
y <- pair.pcs[2,i]
a <- pcs.var[1,i]
b <- pcs.var[2,i]
p <- ggplot(mapping = aes(
x = pcs[,x],
y = pcs[,y],
fill = group)) +
xlab(paste0('PC', a, ' (',pc.var[a], '%)')) +
ylab(paste0('PC', b, ' (',pc.var[b], '%)')) +
geom_point(
aes(fill = group),
pch = 21,
color = strokeColor,
stroke = strokeSize,
size = pointSize,
alpha = alpha) +
scale_x_continuous(breaks = scales::pretty_breaks(n = 5)) +
scale_y_continuous(breaks = scales::pretty_breaks(n = 5)) +
theme(
panel.background = element_blank(),
axis.line = element_line(colour = "black", size = 1.1),
legend.position = "none",
axis.text.x = element_text(size = 10),
axis.text.y = element_text(size = 10),
axis.title.x = element_text(size = 14),
axis.title.y = element_text(size = 14)) +
scale_fill_manual(values = color, name = group.name)
}
p <- p + ggplot2::theme(legend.position = "none")
xdens <- cowplot::axis_canvas(p, axis = "x")+
ggplot2::geom_density(
mapping = ggplot2::aes(
x = pcs[,x],
fill = group),
alpha = 0.7,
size = 0.2
) +
ggplot2::theme(legend.position = "none") +
ggplot2::scale_fill_manual(values = color)
ydens <- cowplot::axis_canvas(
p,
axis = "y",
coord_flip = TRUE) +
ggplot2::geom_density(
mapping = ggplot2::aes(
x = pcs[,y],
fill = group),
alpha = 0.7,
size = 0.2) +
ggplot2::theme(legend.position = "none") +
ggplot2::scale_fill_manual(name = group.name, values = color) +
ggplot2::coord_flip()
p1 <- insert_xaxis_grob(
p,
xdens,
grid::unit(.2, "null"),
position = "top"
)
p2 <- insert_yaxis_grob(
p1,
ydens,
grid::unit(.2, "null"),
position = "right"
)
pList[[i]] <- ggdraw(p2)
}
pList[[i+1]] <- le
return(pList)
}
sample.info <- as.data.frame(SummarizedExperiment::colData(data))
data.set.names <- names(SummarizedExperiment::assays(data))
if (group == "Time"){
if(plot_type == "DensityPlot"){
currentCols <- RColorBrewer::brewer.pal(8, "Dark2")[-5]
years.colors <- currentCols[1:length(unique(sample.info$Year))]
pca.plots.time <- lapply(
data.set.names,#tcga.harmonized,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Time',
group = sample.info$Year,
color = years.colors,#unique(sample.info$Year),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4, top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Year
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
}
else
if (group == "Tissue"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Tissue',
group = sample.info$Tissues,
color = c("#252525","#D9D9D9"),#c('red', 'blue'),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Tissues
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "Plate"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Plate',
group = sample.info$Plates,
color = unique(factor(sample.info$Plates)),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Plates
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "TSS"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'TSS',
group = sample.info$TSS,
color = unique(factor(sample.info$TSS)),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$TSS
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
} else
if (group == "Center"){
if(plot_type == "DensityPlot"){
pca.plots.time <- lapply(
data.set.names,
function(x){
pcs <- pca.data[[x]]
p <- .scatter.density.pc(
pcs = pcs$sing.val$u[,pcs.no],
pc.var = pcs$var,
pcs.no = pcs.no,
group.name = 'Center',
group = sample.info$Center,
color = unique(sample.info$Center),
strokeSize = .2,
pointSize = 3,
strokeColor = 'gray30',
alpha = .6)
do.call(
gridExtra::grid.arrange,
c(p,
ncol = 4,
top = x)
)
})
} else if (plot_type == "BoxPlot"){
for (i in data.set.names){
to.plot.pc <- pca.data[[i]]$sing.val$u
to.plot.pc <- as.data.frame(to.plot.pc)
to.plot.pc <- to.plot.pc[,pcs.no]
colnames(to.plot.pc) <- paste0('pc', pcs.no)
to.plot.pc$variable = sample.info$Center
to.plot.pc <- to.plot.pc %>%
tidyr::pivot_longer(-variable, names_to = 'pcs', values_to = 'var') %>%
data.frame(.)
p <- ggplot(to.plot.pc, aes(x = variable, y = var)) +
geom_boxplot()+
facet_wrap(~pcs) +
ylab('PC') +
ggtitle(i) +
theme(
panel.background = element_blank(),
plot.title = element_text(size = 22),
axis.line = element_line(colour = 'black', size = 1),
axis.title.x = element_text(size = 16),
axis.title.y = element_text(size = 16),
axis.text.x = element_text(size = 12),
axis.text.y = element_text(size = 12),
legend.text = element_text(size = 12),
legend.title = element_text(size = 14),
strip.text.x = element_text(size = 20),
strip.text = element_text(size = 22))
print(p)
}
}
}
#return(data.set.names)
}
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