/
sbs_plot.R
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sbs_plot.R
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cbind.fill <- function(...){
nm <- list(...)
nm <- lapply(nm, as.matrix)
n <- max(sapply(nm, nrow))
do.call(cbind, lapply(nm, function (x)
rbind(x, matrix(, n-nrow(x), ncol(x)))))
}
make_descr_label = function(plot, descr)
{
descrLabel <- ggdraw() + draw_label(descr, fontface='bold', angle = 0)
pe = cowplot::plot_grid(descrLabel, plot, ncol=1, nrow=2, labels=NULL,rel_heights = c(0.1, 1),
align = "h", axis = "l")
return(pe)
}
makeSideBySideDotPlot = function(scobj, plotElems, featureGenes = c("Csf1r", "Chil3"), group.by="cellnames_manual", col.min = -3, col.max = 3, cols = c("grey", "blue"), scaled=T, features.rotate=T, rel.width.legend=0.05, plot.title="")
{
featureGenes.orig = featureGenes
featureGenes = intersect(featureGenes, rownames(scobj))
plot_list = list()
plot_orig_list = list()
allFoundFeatures = c()
allFoundGroups = c()
elemCount = 0
for (plotName in names(plotElems))
{
print(plotName)
plotData = plotElems[[plotName]]
plotCells = plotData$cells
plotDescr = plotData$label
if (scaled)
{
plotElem_orig = DotPlot(subset(scobj, cells=plotCells), features=featureGenes, group.by = group.by, col.min = col.min, col.max=col.max, cols=cols, scale=scaled)
} else {
plotElem_orig = DotPlot(subset(scobj, cells=plotCells), features=featureGenes, group.by = group.by, cols=cols, scale=scaled)
# https://github.com/satijalab/seurat/issues/2798
plotElem_orig$layers[[1]] <- NULL # remove original geom_point layer where the color scale is hard-coded to use scaled average expression
plotElem_orig$data[plotElem_orig$data$avg.exp>col.max, 'avg.exp'] = col.max
plotElem_orig$data[plotElem_orig$data$avg.exp<col.min, 'avg.exp'] = col.min
plotElem_orig <- plotElem_orig +
geom_point(mapping = aes_string(size = 'pct.exp', color = 'avg.exp')) +
guides(color = guide_colorbar(title = 'Average Expression'))
}
allFoundFeatures = unique(c(allFoundFeatures, as.character(plotElem_orig$data$features.plot)))
allFoundGroups = unique(c(allFoundGroups, as.character(plotElem_orig$data$id)))
plotElem_orig = plotElem_orig + scale_color_gradient(limits=c(col.min, col.max), low = cols[1], high = cols[2])
plotElem_orig = plotElem_orig + theme(axis.title.x=element_blank(), axis.title.y=element_blank(), legend.position = "none")
if (features.rotate)
{
plotElem_orig= plotElem_orig + theme(axis.text.x = element_text(angle = 90, hjust = 1, vjust=0.5))
}
plot_orig_list[[plotName]] = plotElem_orig
}
if (scaled)
{
# calculate avg.exp.scaled2 for each feature
for (featureName in allFoundFeatures)
{
allUnscaledValues = data.frame()
for (plotName in names(plot_orig_list))
{
pData = plot_orig_list[[plotName]]$data
newDF = data.frame(pData[ pData$features.plot==featureName, ]$avg.exp)
colnames(newDF) = c(plotName)
allUnscaledValues = cbind.fill(allUnscaledValues, newDF)
}
sampleNames = colnames(allUnscaledValues)
allUnscaledValues = as.data.frame(allUnscaledValues)
allUnscaledValues$rnames = as.numeric(rownames(allUnscaledValues))
allUnscaledLong = allUnscaledValues %>% gather(Type, Value, sampleNames)
allUnscaledLong$Value = scale(allUnscaledLong$Value)
allScaledValues = allUnscaledLong %>% spread(Type, Value) %>% arrange( order(rnames))
allScaledValues
for (plotName in names(plot_orig_list))
{
plotElem_orig = plot_orig_list[[plotName]]
pData = plotElem_orig$data
# https://github.com/satijalab/seurat/issues/2798
plotElem_orig$layers[[1]] <- NULL # remove original geom_point layer where the color scale is hard-coded to use scaled average expression
plotElem_orig$data[plotElem_orig$data$features.plot==featureName, "avg.exp.scaled2"] = allScaledValues[!is.na(allScaledValues[, plotName]),plotName]
plot_orig_list[[plotName]] = plotElem_orig
}
}
for (plotName in names(plot_orig_list))
{
for (featureName in allFoundFeatures)
{
plotElem_orig = plot_orig_list[[plotName]]
pData = plotElem_orig$data
for (groupName in allFoundGroups)
{
subdf = pData[pData$id == groupName & pData$features.plot == featureName,]
if (nrow(subdf) == 0)
{
print(paste(plotName, featureName, groupName))
addDF = data.frame(avg.exp=0, pct.exp=0, features.plot=featureName, id=groupName, avg.exp.scaled=col.min, avg.exp.scaled2=col.min, stringsAsFactors = FALSE)
rownames(addDF) = featureName
plotElem_orig$data$id <- as.character(plotElem_orig$data$id)
plotElem_orig$data = rbind(plotElem_orig$data, addDF)
plotElem_orig$data$id <- as.factor(plotElem_orig$data$id)
plot_orig_list[[plotName]] = plotElem_orig
}
}
}
}
for (plotName in names(plot_orig_list))
{
plotElem_orig = plot_orig_list[[plotName]]
pData = plotElem_orig$data
plotElem_orig$data[plotElem_orig$data$avg.exp.scaled2>col.max, 'avg.exp.scaled2'] = col.max
plotElem_orig$data[plotElem_orig$data$avg.exp.scaled2<col.min, 'avg.exp.scaled2'] = col.min
plotElem_orig <- plotElem_orig +
geom_point(mapping = aes_string(size = 'pct.exp', color = 'avg.exp.scaled2')) +
guides(color = guide_colorbar(title = 'Average Scaled Expression'))
plotElem_orig = plotElem_orig + scale_color_gradient(limits=c(col.min, col.max), low = cols[1], high = cols[2])
plotElem_orig = plotElem_orig + theme(axis.title.x=element_blank(), axis.title.y=element_blank(), legend.position = "none")
plot_orig_list[[plotName]] = plotElem_orig
}
}
elemCount = 0
plot_list=list()
for (plotName in names(plot_orig_list))
{
plotElem_orig = plot_orig_list[[plotName]]
elemCount = elemCount + 1
plotElem = plotElem_orig + theme(
axis.text.y = element_blank(),
panel.grid.major.x = element_line( size=.1, color="black" ),
axis.line.y = element_line(size = 0),
axis.ticks.length.y = unit(0, "points")
)
pe = make_descr_label(plotElem, plotElems[[plotName]]$label)
plot_list[[plotName]] = pe
}
legendDescr = 'Average Expression'
if (scaled)
{
legendDescr = 'Average Scaled Expression'
}
# extract a legend that is laid out horizontally #
legend_b <- get_legend(
plotElem_orig +
guides(color = guide_colorbar(title = legendDescr, direction="horizontal"))+ #guide_legend(nrow = 1, override.aes = list(size=6)))+
theme(legend.position = "bottom")
)
title <- ggdraw() + draw_label(plot.title, fontface='bold')
plotElem_new = plot_orig_list[[names(plot_orig_list)[[1]]]]
plotElem_new$layers[[1]] = NULL
pa = plotElem_new + theme(axis.text.x=element_text(colour = "white")) #+ xlim("", "B")
pal = make_descr_label(pa, "")
plist = list()
plist[["Legend"]] = pal
for (le in names(plot_list))
{
plist[[le]] = plot_list[[le]]
}
ap=cowplot::plot_grid(
plotlist = plist,
labels = NULL,
nrow=1, rel_widths = c(rel.width.legend, rep(0.1, length(plot_list))),
align = "v", axis="bt"
)
fp = cowplot::plot_grid(title, ap, legend_b, ncol = 1, rel_heights = c(0.05, 1, 0.1) )
return(fp)
}