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| library(ggplot2)
library(scattermore)
data <- read.csv("genomic-data-visualization/data/Visium_Cortex_varnorm.csv.gz")
pos <- data[, c('x', 'y')]
rownames(pos) <- data[,1]
gexp <- data[, 4:ncol(data)]
rownames(gexp) <- data[,1]
numgenes <- rowSums(gexp)
normgexp <- gexp/numgenes*1e6
mat <- log10(normgexp + 1)
pcs <- prcomp(mat)
library(Rtsne)
set.seed(0)
#emb <- Rtsne(pcs$x[,1:30], dims=2, perplexity=30)$Y
emb <- Rtsne(pcs$x[,1:30], dims=2, perplexity=100)$Y
# markers of interest
markers <- c('Olig1', 'Olig2', 'Pdgfra', 'Osp', 'Mbp', 'Mog', 'Sox10')
markers.have <- intersect(markers, colnames(mat))
markers.have
gs.plot <- lapply(markers.have, function(g) {
df1 <- data.frame(x = emb[,1],
y = emb[,2],
col = mat[,g])
p1 <- ggplot(data = df1,
mapping = aes(x = x, y = y)) +
geom_scattermore(mapping = aes(col = col),
pointsize=2) +
scale_color_viridis_c(option = "plasma")
plot1 <- p1 + labs(x = "tSNE X" , y = "tSNE Y", title=g) +
theme_classic()
return(plot1)
})
gs.plot[1]
gs.plot[2]
set.seed(0)
clus <- kmeans(pcs$x[,1:30], centers = 10)$cluster
df1 <- data.frame(x = emb[,1],
y = emb[,2],
col = as.factor(clus))
p1 <- ggplot(data = df1,
mapping = aes(x = x, y = y)) +
geom_scattermore(mapping = aes(col = col),
pointsize=2)
plot1 <- p1 + labs(x = "tSNE X" , y = "tSNE Y") +
theme_classic()
plot1
df <- reshape2::melt(
data.frame(id=rownames(mat),
mat[, markers.have],
col=as.factor(clus)))
diffgexp.plot <- ggplot(data = df,
mapping = aes(x=col, y=value, fill=col)) +
geom_violin() +
theme_classic() +
facet_grid(variable ~ .)
diffgexp.plot
df2 <- data.frame(x = emb[,1],
y = emb[,2],
col = as.factor(clus==9))
p2 <- ggplot(data = df2,
mapping = aes(x = x, y = y)) +
geom_scattermore(mapping = aes(col = col),
pointsize=2)
plot2 <- p2 + labs(x = "tSNE X" , y = "tSNE Y",
title='Putative Mature Oligodendricytes') +
scale_color_manual(values=c("#eeeeee", "#FF0000")) +
theme_classic()
plot2
df3 <- data.frame(x = pos[,1],
y = pos[,2],
col = as.factor(clus==9))
p3 <- ggplot(data = df3,
mapping = aes(x = x, y = y)) +
geom_scattermore(mapping = aes(col = col),
pointsize=2)
plot3 <- p3 + labs(x = "pos X" , y = "pos Y",
title='Putative Mature Oligodendricytes') +
scale_color_manual(values=c("#eeeeee", "#FF0000")) +
theme_classic()
plot3
# arrange together
lay <- rbind(c(1,2,3),
c(4,5,6),
c(7,8,8),
c(9,8,8),
c(10,8,8))
png("jfan9_Visium_matolig.png", width = 1000, height = 1500)
gridExtra::grid.arrange(gs.plot[[1]], gs.plot[[2]], gs.plot[[3]],
gs.plot[[4]], gs.plot[[5]], gs.plot[[6]],
plot1, diffgexp.plot,
plot2, plot3, layout_matrix=lay)
dev.off()
|
