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Extra_functions.R
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Extra_functions.R
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plotScatter <- function (ff_after,
ff_before = NULL,
channels,
adjust = 1,
title = NULL)
{
set.seed(1)
if (!is.null(ff_before)){
if (!"Original_ID" %in% colnames(ff_before)){
original_ff_new <- PeacoQC:::AppendCellID(ff_before, 1:nrow(ff_before))
to_plot_ff <- original_ff_new
} else{
to_plot_ff <- ff_before
}
idx <- sample(to_plot_ff@exprs[,"Original_ID"],20000 )
ff_sub <- to_plot_ff[to_plot_ff@exprs[,"Original_ID"] %in% idx,]
removed_meas <- setdiff(to_plot_ff@exprs[,"Original_ID"],
ff_after@exprs[,"Original_ID"])
removed_meas <- which(ff_sub@exprs[,"Original_ID"] %in% removed_meas)
} else{
to_plot_ff <- ff_after
idx <- sample(1:nrow(to_plot_ff), 20000)
ff_sub <- to_plot_ff[idx,]
}
channels <- FlowSOM::GetMarkers(to_plot_ff, channels, exact = TRUE)
df <- ff_sub@exprs[,names(channels)] %>% as.data.frame()
colnames(df) <- gsub("-", "", colnames(df))
colors <- c("#0000BF", "#0000FF", "#0080FF", "#00FFFF", "#55FFAA", "#AAFF55",
"#FFFF00", "#FF8000", "#FF0000", "#BF0000")
p <- ggplot(data = df, aes(x = !!sym(colnames(df)[1]), y = !!sym(colnames(df)[2]))) +
ggpointdensity::geom_pointdensity(adjust=adjust) +
ggplot2::scale_color_gradientn(colours =
colors) +
theme_minimal() +
theme(legend.position = "none") +
xlab(channels[1]) +
ylab(channels[2])
if(!is.null(ff_before)){
p <- p + geom_point(data = df[removed_meas,], color = "grey60")
}
if(!is.null(title))
p <- p + ggtitle(title)
return(p)
}
estimateGate <- function (ff, marker_values = list(`FSC-A` = c(min = 60000, max = 125000,
range_min = 50000, range_max = 50000),
`SSC-A` = c(max = 80000,
range_max = 50000)),
plot = FALSE, plot_title = "Gate", tinypeak.removal = 1/25)
{
selection <- rep(TRUE, nrow(ff))
for (m in names(marker_values)) {
cutoffs <- c(flowDensity::deGate(ff, m, all.cuts = TRUE,
tinypeak.removal = tinypeak.removal),
flowDensity::deGate(ff, m, use.upper = TRUE, upper = TRUE))
for (type in c("min", "max")) {
if (!is.na(marker_values[[m]][type])) {
default <- marker_values[[m]][type]
cutoff <- cutoffs[which.min(abs(cutoffs - default))]
if (!is.na(marker_values[[m]][paste0("range_",
type)]) & abs(cutoff - default) > marker_values[[m]][paste0("range_",
type)]) {
cutoff <- default
}
if (type == "min")
selection <- selection & ff@exprs[, m] > cutoff
if (type == "max")
selection <- selection & ff@exprs[, m] < cutoff
marker_values[[m]][type] <- cutoff
}
}
if (!"plot_min" %in% names(marker_values[[m]]))
marker_values[[m]]["plot_min"] <- NA
if (!"plot_max" %in% names(marker_values[[m]]))
marker_values[[m]]["plot_max"] <- NA
}
if (plot) {
p <- list()
for (i in seq(1, length(marker_values), 2)) {
m1 <- names(marker_values)[i]
if (i + 1 <= length(marker_values)) {
m2 <- names(marker_values)[i + 1]
}
else {
m1 <- colnames(ff)[1]
m2 <- names(marker_values)[i]
}
if (!"Original_ID" %in% colnames(ff)) {
ff <- flowCore::fr_append_cols(ff, matrix(seq_len(nrow(ff)),
ncol = 1, dimnames = list(NULL, "Original_ID")))
}
p[[length(p) + 1]] <- filter_plot(ff, ff[selection,
], "", m1, m2) + ggplot2::geom_vline(xintercept = marker_values[[m1]]["min"],
color = c("cyan")) + ggplot2::geom_vline(xintercept = marker_values[[m1]]["max"],
color = c("red")) + ggplot2::geom_hline(yintercept = marker_values[[m2]]["min"],
color = c("cyan")) + ggplot2::geom_hline(yintercept = marker_values[[m2]]["max"],
color = c("red")) + ggplot2::theme_minimal() +
ggplot2::ggtitle(plot_title)
if (!is.na(marker_values[[m1]]["plot_min"]) | !is.na(marker_values[[m1]]["plot_max"]))
p[[length(p)]] <- p[[length(p)]] + ggplot2::xlim(marker_values[[m1]]["plot_min"],
marker_values[[m1]]["plot_max"])
if (!is.na(marker_values[[m2]]["plot_min"]) | !is.na(marker_values[[m2]]["plot_max"]))
p[[length(p)]] <- p[[length(p)]] + ggplot2::ylim(marker_values[[m2]]["plot_min"],
marker_values[[m2]]["plot_max"])
}
return(list(selection = selection, plot = p))
}
else {
return(selection)
}
}
filter_plot <- function (ff_pre, ff_post, title, channel_x, channel_y, n = 10000)
{
df <- data.frame(x = flowCore::exprs(ff_pre)[, channel_x],
y = flowCore::exprs(ff_pre)[, channel_y])
i <- sample(nrow(df), min(n, nrow(df)))
if (!"Original_ID" %in% colnames(flowCore::exprs(ff_pre))) {
ff_pre <- flowCore::fr_append_cols(ff_pre, matrix(seq_len(nrow(df)),
ncol = 1, dimnames = list(NULL, c("Original_ID"))))
}
p <- ggplot2::ggplot(df[i, ], ggplot2::aes(x = .data$x, y = .data$y)) +
ggplot2::geom_point(size = 0.5, color = ifelse(flowCore::exprs(ff_pre)[i,
"Original_ID"] %in% flowCore::exprs(ff_post)[, "Original_ID"],
"blue", "red")) + ggplot2::xlab(paste(flowCore::getChannelMarker(ff_pre,
channel_x), collapse = " ")) + ggplot2::ylab(paste(flowCore::getChannelMarker(ff_pre,
channel_y), collapse = " ")) + ggplot2::theme_minimal() +
ggplot2::theme(legend.position = "none") + ggplot2::ggtitle(paste0(round(flowCore::nrow(ff_post)/flowCore::nrow(ff_pre) *
100, 2), "% ", title))
return(p)
}
plotDens <- function(input,
channels,
level,
plotFile){
plotlist <- list()
for (channel in channels){
plotlist[[length(plotlist)+1]] <- ggplot(data = input, aes(x = !!sym(channel),
color = !!sym(level))) +
stat_density(aes(group = .data$File),
geom = "line", position = "identity",
alpha = 0.2) +
stat_density(aes(group = !!sym(level)),
geom = "line", position = "identity",
alpha = 1) +
xlab(GetMarkers(object = ff,
channels = channel)) +
theme_minimal()
}
pdf(plotFile, width = 20, height = 12)
print(ggarrange(plotlist = plotlist, common.legend = TRUE, nrow = 5, ncol = 5))
dev.off()
}
plotUMAP <- function(input,
level,
plotFile){
p <- ggplot(input, aes(x = UMAP1, y = UMAP2, color = !!sym(level))) +
geom_point() +
theme_minimal()
pdf(plotFile, width = 20, height = 12)
print(p)
dev.off()
}
plotGate <- function(ff,
gate_coord){
gate_df <- data.frame(x = gate_coord[, 1],
y = gate_coord[, 2],
xend = c(gate_coord[-1,1], gate_coord[1,1]),
yend = c(gate_coord[-1,2], gate_coord[1,2]))
channel_x <- colnames(gate_coord)[1]
channel_y <- colnames(gate_coord)[2]
p <- ggplot(as.data.frame(exprs(ff))[sample(nrow(exprs(ff)), 10000),],
aes_string(x = paste0("`", channel_x, "`"), y = paste0("`", channel_y, "`"))) +
geom_point() +
geom_segment(data = gate_df,
aes(x = x, y = y, xend = xend, yend = yend),
color = "red", linewidth = 1.5) +
geom_point(data = gate_df,
aes(x = x, y = y),
color = "red", size = 2.5) +
theme_minimal()
return(p)
}