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library(ggplot2); 
library(reshape)

dat2 = as.data.frame(melt(dat))
dat2$text = signif(dat2$value,2)

p1=ggplot(dat2, aes(x=X2,y=X1, label=text)) + 
  geom_tile(aes(fill=-log10(value)),color="grey60") + 
  scale_fill_gradient(name = '-log10(P)', low = 'white', high = 'red') +
  theme(axis.text.x=element_text(angle=50, size=10, hjust=1)) + ylab("") + xlab("") + 
  geom_text(size=3) + ggtitle("Cell-type Enrichment")

# hclust + heatmap
Seurat_Heatmap_By_Cluster_Hclust_Genes_SetColWidths <- function(
 genes, clusterOrder) {

 print(“Seurat_Heatmap_By_Cluster_Hclust_Genes_SetColWidths”)

 # Subset expression matrix
 exM <- centSO@scale.data
 exM <- exM[row.names(exM) %in% genes, ]

 # Obtain the dendrogram
 dend <- as.dendrogram(hclust(d = dist(exM), method = "ward.D2"))
 dend_data <- dendro_data(dend)
 # Setup the data, so that the layout is inverted (this is more
 # “clear” than simply using coord_flip())
 segment_data <- with(
   segment(dend_data),
   data.frame(x = y, y = x, xend = yend, yend = xend))
 # Use the dendrogram label data to position the gene labels
 gene_pos_table <- with(
   dend_data$labels,
   data.frame(y_center = x, gene = as.character(label), height = 1))
 # Limits for the vertical axes
 gene_axis_limits <- with(
   gene_pos_table,
   c(min(y_center - 0.5 * height), max(y_center + 0.5 * height))) + 0.1 * c(-1, 1) # extra spacing: 0.1
 # Facet dendrogram so it lines up with faceted heatmaps
 segment_data$Facet <- “”

 # Dendrogram plot
 plt_dendr <- ggplot(segment_data) +
   geom_segment(aes(x = x, y = y, xend = xend, yend = yend)) +
   scale_x_reverse(expand = c(0, 0.5)) +
   scale_y_continuous(breaks = gene_pos_table$y_center,
     labels = gene_pos_table$gene,
     limits = gene_axis_limits,
     expand = c(0, 0)) +
   facet_wrap(~Facet) +
   labs(x = “Distance”, y = “”, colour = “”, size = “”) +
   theme_bw() +
   theme(panel.grid.minor = element_blank()) +
   theme(strip.background = element_blank())

 # Heatmap plot
 geneGroupDF <- data.frame(GENE = gene_pos_table$gene, GROUP = “”)
 gg <- Plot_Marker_Genes_Heatmap_SetColWidths(geneGroupDF = geneGroupDF)

 # Combine heatmap and dendrogram
 pg <- plot_grid(plotlist = list(gg_dendr, gg)
   , ncol = 2
   , rel_widths = c(0.2,1), align = ‘h’, axis = ‘t’)

 return(pg)
}

title = "asdM12"
data = as.data.frame(t(M12_betas[,1:16]));   ## Make data frame with Columns for Beta, SEM, Group
data$Col = rownames(data);   #really should be called data$Row
data$Group = as.factor(substr(rownames(data),start = regexpr(".",rownames(data),fixed=T)+1,50))  # Make a factor variable for Group

bp = ggplot(data, aes(x=reorder(Col, as.numeric(Group)), y=Beta, fill=Group))  # Plots groups in alphabetical order

bp + 
	geom_bar(stat="identity") +   
	geom_errorbar(aes(ymin=(Beta - SEM), ymax=(Beta + SEM)), 		position=position_dodge(width=0.8), width=0.25,size=0.25) +   
	ggtitle(title) +   
	theme(plot.title = element_text(size=20, face="bold", vjust=2)) +   
	labs(x="", y="regression beta") +   
	theme(axis.text.x=element_text(angle=50, size=10, hjust=1)) +   	theme(axis.text.y=element_text(size=10, vjust=0.5)) +   
	theme(     
		legend.title = element_text(size=12),    
		plot.title = element_text(size=20, face="bold"),     
		axis.title.x = element_text(size=14, vjust=-0.35, face="bold"), 
		axis.title.y = element_text(size=14, vjust=0.5)   
	)
	
	
	
	colors "#F8766D" "#00BA38" "#	a"
	
	"#F8766D" "#00BA38" "#619CFF"