R/pcaMatrix.R
In joeburns06/hocuspocus: A Suite of Single-Cell RNA-Seq Analysis Tools Built for Dummy Biologists
#' Generate a series of plots comparing the first 10 PCs of a PCA analysis.
#'
#' Takes ExpressionSet object, performs PCA on the transposed expression matrix,
#' then plots the projections of the sample scores on the first 10 PCs.
#'
#' @param cellData ExpressionSet object created with readCells (and preferably
#' transformed with prepCells). It is also helpful to first run
#' reduceGenes_var.
#' @param scree Boolean specifying whether to generate a scree plot showing the
#' amount of variance contributed by each PC.
#' @param center Boolean specifying whether to the center the data prior to PCA.
#' This is generally recommended.
#' @param scale Boolean specifying whether the data should be scaled prior to
#' PCA. This is generally not recommended unless samples have different units
#' (e.g. some samples are counts and some are TPMs).
#' @param groups Character string specifying the title of the column in pData
#' that contains the names of the groups to which each sample belongs. The
#' dots representing each sample in the plots will be colored by group. The
#' column length should be the same length as the number of samples.
#' @param values Character string specifying the title of the column in pData
#' that contains a vector of numeric values to be plotted as a color gradient
#' on the dots in the plots. The column length should be the same length as
#' the number of samples. Gene and values cannot be specified simultaneously.
#' If groups and values are both specified, gene will be used for coloring.
#' Set bubble to TRUE to display group information as well.
#' @param gene Character string specifying a gene whose expression values will
#' be plotted a color gradient on the dots in the plots. One gene name should
#' be specified, and the gene must be present within the expression table.
#' Gene and values cannot be specified simultaneously. If groups and gene are
#' both specified, gene will be used for coloring. Set bubble to TRUE to
#' display group information as well.
#' @param colors Vector of character strings of length 2 specifying the color range for values or gene. If
#' not specified, a default black-to-yellow color gradient will be used.
#' @param logNumeric Boolean specifying whether the numbers in values should be
#' transformed to log2 space.
#' @param refPC Character string specifying the PC to be used as the reference
#' PC that is plotted on the x-axis of every plot.
#' @param alpha Numeric specifying the transparency (from 0 to 1) level of the
#' dot colors.
#' @param dotsize Numeric specifying the size of the dots in the plots.
#' @param bubble Boolean specifying whether dots of different sizes should be
#' plotted to display information about another variable on the plot.
#' @param bubbleSizes Vector of numerics specifying the dot sizes for each group
#' within groups. Length of bubbleSizes should be the same length as groups.
#' If bubbleSizes is not specified, default sizes will be generated according
#' to the levels in the groups column. Useful for displaying group
#' information along with values or gene. Additionally, can be used to
#' indicate additional information about groups. E.g. if the levels in groups
#' are 'A1', 'B1', 'C2', and 'D2', bubbleSizes could be c(3,3,6,6) to indicate
#' the '1' and '2' components of the groups with different dot sizes.
#' @param print Boolean specifying whether the genes with the most positive and
#' negative loadings on each of the 10 PCs should be printed in the terminal
#' window.
#' @param printNum Integer specifying the number of genes from each PC to print.
#' @param save Boolean specifying whether to save the resultant plots as a .tiff
#' file.
#' @return Matrix of PCA plots for the first 10 PCs.
#' @export
pcaMatrix <- function(cellData, scree = FALSE, center = TRUE, scale = FALSE, ICA=FALSE, groups, values, gene, colors, logNumeric = TRUE, refPC = "PC1", alpha = 0.7, dotsize = 2,
bubble = FALSE, bubbleSizes, print = FALSE, printNum = 50, save = FALSE) {
if (.Platform$OS.type == "windows") {
quartz <- function() windows()
}
if (cellData@logData$prepCells[1] == "No") {
warning("It would be wise to run prepCells prior to pcaMatrix.", call. = FALSE)
}
if (!missing(groups) && !all((groups %in% colnames(pData(cellData))))) {
stop("The column name specified for groups is not found in phenoData. If absent, add a column to phenoData containing the group for each cell, even if it only consists of 1 group.",
call. = FALSE)
}
if (!missing(values) && !all((values %in% colnames(pData(cellData))))) {
stop("The column name specified for values is not found in phenoData.",
call. = FALSE)
}
if (!missing(groups) && !all((names(cData(cellData)) %in% colnames(pData(cellData))))) {
stop("Some or all of the column names in colorData do not have matching column names in phenoData.",
call. = FALSE)
}
PCA.allgenes <- prcomp(t(exprs(cellData)), center = center, scale. = scale, save = FALSE)
if (scree == TRUE) {
quartz()
screeplot(PCA.allgenes, type = "lines", main = "Scree Plot")
if (save == TRUE) {
quartz(type = "pdf", file = "Scree Plot.pdf")
screeplot(PCA.allgenes, type = "lines")
dev.off
}
}
if (ICA==FALSE){
comp2 <- data.frame(PCA.allgenes$x[, 1:10])
comp.cell.type2 <- comp2
}
if (ICA==TRUE){
ica1 <- fastICA::fastICA(t(exprs_table), 10)
comp2 <- data.frame(ica1$S[, 1:10])
comp2["y"] <- seq(0, 0, length.out = length(samples[, groups]))
comp.cell.type2 <- comp2
}
if (missing(groups)) {
cell_colors <- "blue"
comp.cell.type2["Cell_Type"] <- rep("All", nrow(pData(cellData)))
}
if (!missing(groups)) {
cell_colors <- data.frame(cellData@colorData[[groups]], stringsAsFactors = FALSE)
cell_colors <- as.character(cell_colors[!apply(is.na(cell_colors) | cell_colors == "", 1, all), ])
groupz <- data.frame(pData(cellData)[, groups], stringsAsFactors = FALSE)
comp.cell.type2["Cell_Type"] <- factor(groupz[, colnames(groupz)], levels = unique(groupz[, colnames(groupz)]), ordered = FALSE)
}
if (bubble == TRUE) {
if (missing(bubbleSizes)) {
sizes <- 1:length(levels(comp.cell.type2$Cell_Type))
}
if (!missing(bubbleSizes)) {
sizes <- bubbleSizes
}
}
if (bubble == FALSE) {
sizes <- vector(length = length(cell_colors))
sizes[1:length(cell_colors)] <- dotsize
}
if (missing(values) && missing(gene)) {
if (bubble == TRUE) {
warning("Bubble sizes currently reflect the number of levels in groups and are not adding additional information to the plot.", call. = FALSE)
}
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (!missing(values)) {
if (!missing(gene)) {
stop("Cannot specify both values and gene.", call. = FALSE)
}
if (!missing(colors)){
cell_colors <- colors
}
if (length(cell_colors) != 2) {
warning("Specify a vector of two colors to control color, using default colors instead", call. = FALSE)
cell_colors[1:2] <- c("black", "yellow")
}
valuez <- data.frame(pData(cellData)[, values], stringsAsFactors = FALSE)
if (logNumeric == TRUE) {
valuez <- log2(valuez)
}
comp.cell.type2["Values"] <- valuez
if (bubble == TRUE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (bubble == FALSE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
}
if (!missing(gene)) {
if (!missing(values)) {
stop("Cannot specify both values and gene.", call. = FALSE)
}
if (!gene %in% row.names(exprs(cellData))) {
stop("Specified gene is not present in expression table", call. = FALSE)
}
if (!missing(colors)){
cell_colors <- colors
}
if (length(cell_colors) != 2) {
warning("Specify a vector of two colors to control color, using default colors instead", call. = FALSE)
cell_colors[1:2] <- c("black", "yellow")
}
genez <- data.frame(exprs(cellData)[gene, ], stringsAsFactors = FALSE)[, 1]
comp.cell.type2[gene] <- genez
if (bubble == TRUE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (bubble == FALSE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
}
if (print == TRUE) {
if (printNum > nrow(exprs(cellData))) {
stop("There are fewer genes than printNum in the expression matrix.")
}
n <- printNum/2
comp3 <- data.frame(PCA.allgenes$rotation[, 1:10])
comp3_order <- apply(comp3, 2, order, decreasing = TRUE)
terminal_output <- data.frame()
for (i in 1:10) {
terminal_output[1:nrow(comp3), i] <- row.names(comp3)[comp3_order[, i]]
}
colnames(terminal_output) <- colnames(comp3)
terminal_output_final <- terminal_output[c(1:n, (nrow(terminal_output) - n):nrow(terminal_output)), ]
print(terminal_output_final)
}
}
joeburns06/hocuspocus documentation built on May 19, 2019, 2:59 p.m.
R Package Documentation
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#' Generate a series of plots comparing the first 10 PCs of a PCA analysis.
#'
#' Takes ExpressionSet object, performs PCA on the transposed expression matrix,
#' then plots the projections of the sample scores on the first 10 PCs.
#'
#' @param cellData ExpressionSet object created with readCells (and preferably
#' transformed with prepCells). It is also helpful to first run
#' reduceGenes_var.
#' @param scree Boolean specifying whether to generate a scree plot showing the
#' amount of variance contributed by each PC.
#' @param center Boolean specifying whether to the center the data prior to PCA.
#' This is generally recommended.
#' @param scale Boolean specifying whether the data should be scaled prior to
#' PCA. This is generally not recommended unless samples have different units
#' (e.g. some samples are counts and some are TPMs).
#' @param groups Character string specifying the title of the column in pData
#' that contains the names of the groups to which each sample belongs. The
#' dots representing each sample in the plots will be colored by group. The
#' column length should be the same length as the number of samples.
#' @param values Character string specifying the title of the column in pData
#' that contains a vector of numeric values to be plotted as a color gradient
#' on the dots in the plots. The column length should be the same length as
#' the number of samples. Gene and values cannot be specified simultaneously.
#' If groups and values are both specified, gene will be used for coloring.
#' Set bubble to TRUE to display group information as well.
#' @param gene Character string specifying a gene whose expression values will
#' be plotted a color gradient on the dots in the plots. One gene name should
#' be specified, and the gene must be present within the expression table.
#' Gene and values cannot be specified simultaneously. If groups and gene are
#' both specified, gene will be used for coloring. Set bubble to TRUE to
#' display group information as well.
#' @param colors Vector of character strings of length 2 specifying the color range for values or gene. If
#' not specified, a default black-to-yellow color gradient will be used.
#' @param logNumeric Boolean specifying whether the numbers in values should be
#' transformed to log2 space.
#' @param refPC Character string specifying the PC to be used as the reference
#' PC that is plotted on the x-axis of every plot.
#' @param alpha Numeric specifying the transparency (from 0 to 1) level of the
#' dot colors.
#' @param dotsize Numeric specifying the size of the dots in the plots.
#' @param bubble Boolean specifying whether dots of different sizes should be
#' plotted to display information about another variable on the plot.
#' @param bubbleSizes Vector of numerics specifying the dot sizes for each group
#' within groups. Length of bubbleSizes should be the same length as groups.
#' If bubbleSizes is not specified, default sizes will be generated according
#' to the levels in the groups column. Useful for displaying group
#' information along with values or gene. Additionally, can be used to
#' indicate additional information about groups. E.g. if the levels in groups
#' are 'A1', 'B1', 'C2', and 'D2', bubbleSizes could be c(3,3,6,6) to indicate
#' the '1' and '2' components of the groups with different dot sizes.
#' @param print Boolean specifying whether the genes with the most positive and
#' negative loadings on each of the 10 PCs should be printed in the terminal
#' window.
#' @param printNum Integer specifying the number of genes from each PC to print.
#' @param save Boolean specifying whether to save the resultant plots as a .tiff
#' file.
#' @return Matrix of PCA plots for the first 10 PCs.
#' @export
pcaMatrix <- function(cellData, scree = FALSE, center = TRUE, scale = FALSE, ICA=FALSE, groups, values, gene, colors, logNumeric = TRUE, refPC = "PC1", alpha = 0.7, dotsize = 2,
bubble = FALSE, bubbleSizes, print = FALSE, printNum = 50, save = FALSE) {
if (.Platform$OS.type == "windows") {
quartz <- function() windows()
}
if (cellData@logData$prepCells[1] == "No") {
warning("It would be wise to run prepCells prior to pcaMatrix.", call. = FALSE)
}
if (!missing(groups) && !all((groups %in% colnames(pData(cellData))))) {
stop("The column name specified for groups is not found in phenoData. If absent, add a column to phenoData containing the group for each cell, even if it only consists of 1 group.",
call. = FALSE)
}
if (!missing(values) && !all((values %in% colnames(pData(cellData))))) {
stop("The column name specified for values is not found in phenoData.",
call. = FALSE)
}
if (!missing(groups) && !all((names(cData(cellData)) %in% colnames(pData(cellData))))) {
stop("Some or all of the column names in colorData do not have matching column names in phenoData.",
call. = FALSE)
}
PCA.allgenes <- prcomp(t(exprs(cellData)), center = center, scale. = scale, save = FALSE)
if (scree == TRUE) {
quartz()
screeplot(PCA.allgenes, type = "lines", main = "Scree Plot")
if (save == TRUE) {
quartz(type = "pdf", file = "Scree Plot.pdf")
screeplot(PCA.allgenes, type = "lines")
dev.off
}
}
if (ICA==FALSE){
comp2 <- data.frame(PCA.allgenes$x[, 1:10])
comp.cell.type2 <- comp2
}
if (ICA==TRUE){
ica1 <- fastICA::fastICA(t(exprs_table), 10)
comp2 <- data.frame(ica1$S[, 1:10])
comp2["y"] <- seq(0, 0, length.out = length(samples[, groups]))
comp.cell.type2 <- comp2
}
if (missing(groups)) {
cell_colors <- "blue"
comp.cell.type2["Cell_Type"] <- rep("All", nrow(pData(cellData)))
}
if (!missing(groups)) {
cell_colors <- data.frame(cellData@colorData[[groups]], stringsAsFactors = FALSE)
cell_colors <- as.character(cell_colors[!apply(is.na(cell_colors) | cell_colors == "", 1, all), ])
groupz <- data.frame(pData(cellData)[, groups], stringsAsFactors = FALSE)
comp.cell.type2["Cell_Type"] <- factor(groupz[, colnames(groupz)], levels = unique(groupz[, colnames(groupz)]), ordered = FALSE)
}
if (bubble == TRUE) {
if (missing(bubbleSizes)) {
sizes <- 1:length(levels(comp.cell.type2$Cell_Type))
}
if (!missing(bubbleSizes)) {
sizes <- bubbleSizes
}
}
if (bubble == FALSE) {
sizes <- vector(length = length(cell_colors))
sizes[1:length(cell_colors)] <- dotsize
}
if (missing(values) && missing(gene)) {
if (bubble == TRUE) {
warning("Bubble sizes currently reflect the number of levels in groups and are not adding additional information to the plot.", call. = FALSE)
}
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_fill_manual(name = "Cell Type", values = cell_colors) + scale_size_manual(name = "Cell Type",
values = sizes) + guides(fill = guide_legend("Cell Type"), color = guide_legend("Cell Type"), size = guide_legend("Cell Type")) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (!missing(values)) {
if (!missing(gene)) {
stop("Cannot specify both values and gene.", call. = FALSE)
}
if (!missing(colors)){
cell_colors <- colors
}
if (length(cell_colors) != 2) {
warning("Specify a vector of two colors to control color, using default colors instead", call. = FALSE)
cell_colors[1:2] <- c("black", "yellow")
}
valuez <- data.frame(pData(cellData)[, values], stringsAsFactors = FALSE)
if (logNumeric == TRUE) {
valuez <- log2(valuez)
}
comp.cell.type2["Values"] <- valuez
if (bubble == TRUE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "Values", size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend("Values"), size = guide_legend("Groups")) +
scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35, "cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (bubble == FALSE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = "Values"), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = "Values")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
}
if (!missing(gene)) {
if (!missing(values)) {
stop("Cannot specify both values and gene.", call. = FALSE)
}
if (!gene %in% row.names(exprs(cellData))) {
stop("Specified gene is not present in expression table", call. = FALSE)
}
if (!missing(colors)){
cell_colors <- colors
}
if (length(cell_colors) != 2) {
warning("Specify a vector of two colors to control color, using default colors instead", call. = FALSE)
cell_colors[1:2] <- c("black", "yellow")
}
genez <- data.frame(exprs(cellData)[gene, ], stringsAsFactors = FALSE)[, 1]
comp.cell.type2[gene] <- genez
if (bubble == TRUE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = gene, size = "factor(Cell_Type,levels=unique(Cell_Type),ordered=FALSE)"),
shape = 21, color = "black", alpha = alpha) + scale_size_manual(name = "Groups", values = sizes) + guides(color = guide_legend(title = gene),
size = guide_legend("Groups")) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
if (bubble == FALSE) {
g1 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC1", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g2 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC2", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g3 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC3", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g4 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC4", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g5 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC5", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g6 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC6", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g7 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC7", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g8 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC8", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
g9 <- ggplot(comp.cell.type2) + geom_point(aes_string(x = refPC, y = "PC9", fill = gene), size = dotsize, shape = 21, color = "black", alpha = alpha) +
guides(color = guide_legend(title = gene)) + scale_fill_gradient(low = cell_colors[1], high = cell_colors[2]) + theme(legend.key.size = grid::unit(0.35,
"cm"), legend.text = element_text(size = 8))
if (save == TRUE) {
PCA_grob <- arrangeGrob(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
ggsave(PCA_grob, file = paste("PCA Matrix.tiff"))
}
quartz()
PCA_grid <- grid.arrange(g1, g2, g3, g4, g5, g6, g7, g8, g9, ncol = 3)
}
}
if (print == TRUE) {
if (printNum > nrow(exprs(cellData))) {
stop("There are fewer genes than printNum in the expression matrix.")
}
n <- printNum/2
comp3 <- data.frame(PCA.allgenes$rotation[, 1:10])
comp3_order <- apply(comp3, 2, order, decreasing = TRUE)
terminal_output <- data.frame()
for (i in 1:10) {
terminal_output[1:nrow(comp3), i] <- row.names(comp3)[comp3_order[, i]]
}
colnames(terminal_output) <- colnames(comp3)
terminal_output_final <- terminal_output[c(1:n, (nrow(terminal_output) - n):nrow(terminal_output)), ]
print(terminal_output_final)
}
}
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