ggplot2 - R combining ggplot with dlply -

i have following data frame

structure(list(g1 = c(68, 68.6, 66.6, 73.1, 51.6, 50.1, 64.1,  73, 63.7, 43.2, 62.3, 59.2, 67.5, 68.2, 54.6, 67.9, 56.5, 54.2,  67.3, 68, 68.4, 67.9, 73.3, 51.7, 50.3, 63.9, 73.9, 64, 42.9,  62.5, 59.3, 66.7, 68.4, 54, 68.2, 56.8, 54.5, 67, 53.2, 41.4,  53, 52.3, 41, 37.4, 56.9, 65.3, 36.2, 35.3, 36.1, 32.5, 56.5,  47.7, 39.4, 59.6, 38.1, 24.2, 30.2, 68.5, 68.9, 70.7, 74.9, 53.4,  51.6, 65.9, 75.7, 64.7, 42.8, 61.4, 60.8, 69.5, 68.7, 55.9, 70.7,  59.5, 51.1, 69.5), g2 = c(79.8, 72.2, 73.5, 74.4, 50.4, 54.8,  63.1, 70.4, 63.6, 45.1, 65.3, 49.4, 65.3, 76.2, 51, 63.9, 58.7,  57.8, 67, 79.6, 72.1, 73.9, 74.7, 50.5, 55.1, 62.8, 70.5, 63.3,  44.6, 65.5, 48.9, 64.9, 76.3, 50.6, 64.8, 58.6, 58.3, 67.4, 51.2,  37.7, 49.1, 53.7, 44.6, 37.3, 54.9, 64.1, 33.8, 31.9, 34.2, 30.3,  56.2, 44.6, 38.2, 63.2, 35.8, 26.5, 27.6, 80.6, 71.6, 75.4, 77.1,  52.4, 56.3, 66, 72.3, 64.5, 38.2, 64.3, 49.2, 66.9, 77.1, 52.4,  67.5, 59.6, 55.6, 69.9), s1 = c(75.1, 65.9, 72.7, 68.8, 49, 57.5,  66.5, 74.1, 60.9, 51.8, 58, 64.3, 71.1, 71.4, 58.9, 62.2, 58,  57.7, 58.6, 75.2, 66, 73.2, 69.7, 48.9, 57.7, 66.5, 74.7, 60.8,  51.4, 58.9, 65.5, 70.5, 71.4, 58.9, 65.1, 60.8, 57.7, 58.4, 54.3,  40.2, 52.6, 60.5, 42.6, 34.1, 55, 64.7, 36.3, 32.5, 39, 38.8,  58.1, 48, 40.5, 61, 40, 26.4, 28.8, 76.4, 66.5, 73.9, 72, 50.7,  59.2, 69.9, 76.3, 62.4, 50, 58.5, 66.6, 73.7, 72.3, 62.6, 69.6,  62.7, 57.9, 61.1), s2 = c(76.6, 71.6, 71.2, 72.7, 51.6, 56.7,  65.9, 73.5, 63.6, 55.2, 62.6, 62.2, 69.1, 71.1, 56.8, 61, 61.7,  60, 55.7, 76.9, 71.6, 72.3, 73.2, 51.7, 56.8, 64.5, 74.9, 63.6,  51.3, 63, 62.8, 68.7, 71.3, 56.8, 64.2, 62.8, 60.4, 55.8, 53.6,  42.5, 50, 54.4, 42.2, 36.4, 57.7, 64.1, 35.1, 30.8, 39.1, 37.4,  58.7, 47.8, 42, 58.8, 39.4, 24.2, 28.2, 78.2, 73.3, 72.3, 75.6,  53.4, 57.8, 68.3, 76.6, 63.7, 51.7, 63.4, 63.3, 71.5, 72.3, 60.2,  67.1, 65.5, 58.2, 59.1), method = structure(c(4l, 4l, 4l, 4l,  4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 4l, 3l,  3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l, 3l,  3l, 3l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l, 2l,  2l, 2l, 2l, 2l, 2l, 1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l,  1l, 1l, 1l, 1l, 1l, 1l, 1l, 1l), .label = c("simple_2_roi", "single_roi",  "wig_drawn_bg", "wig_method"), class = "factor")), .names = c("g1",  "g2", "s1", "s2", "method"), class = "data.frame", row.names = c(na,  -76l)) 

what produce correlation heatmap (lower triangle only) data set based on variable method.

i can required plot data using following code

library(reshape2) library(ggplot2) c = cor(df[sapply(df,is.numeric)]) cordf.m = melt(cor(df[sapply(df,is.numeric)])) df.lower = subset(cordf.m[lower.tri(c),],var1 != var2) df.ids <- subset(cordf.m, var1 == var2) ggplot(data=df.lower, aes(x=var1,y=var2,fill=value)) + geom_tile() + theme_bw() + geom_text(aes(label = sprintf("%1.2f",value)), vjust = 1) + geom_text(data=df.ids,aes(label=var1)) + scale_fill_gradient2(midpoint=0.8,low='white',high='steelblue') + xlab(null) + ylab(null) + theme(axis.text.x=element_blank(),axis.text.y=element_blank(), axis.ticks=element_blank(),panel.border=element_blank(),legend.position='none')+ggtitle("all data") 

which gives following graph

i can basic correlation heatmap per method using dlply

dlply(df, .(method), function (x1) { ggplot(melt(cor(x1[sapply(x1,is.numeric)])), aes(x=var1,y=var2,fill=value)) + geom_tile(aes(fill = value),colour = "white") + geom_text(aes(label = sprintf("%1.2f",value)), vjust = 1) + theme_bw() +  scale_fill_gradient2(midpoint=0.8,low = "white", high = "steelblue")}) 

however, stuck few issues

(i) how show equivalent plot above each method - i.e lower triangle (ii) how can make ggtitle equal method name e.g simple_2_roi,.. each graph

(iii) use stars highlight significance of each correlation done here. how can data set (i tried p <- cor.pval(iris.. error message cor.pval not found

---

the following gets me closer want

plots <- dlply(df, .(method), function (x1) {     ggplot(subset(melt(cor(x1[sapply(x1,is.numeric)]))[lower.tri(c),],var1 != var2),            aes(x=var1,y=var2,fill=value)) + geom_tile(aes(fill = value),colour = "white") +         geom_text(aes(label = sprintf("%1.2f",value)), vjust = 1) +          theme_bw() +         scale_fill_gradient2(midpoint=0.7,low = "white", high = "steelblue") + xlab(null)+ylab(null) + theme(axis.text.x=element_blank(),axis.text.y=element_blank(), axis.ticks=element_blank(),panel.border=element_blank(),legend.position='none') + ggtitle(x1$method) + theme(plot.title = element_text(lineheight=1,face="bold")) + geom_text(data = subset(melt(cor(x1[sapply(x1,is.numeric)])),var1==var2),aes(label=var1) ) }) 

however, cannot correlation stars on plot

any pointers?

i have achieved following solution (though unable achieve significance stars)

plots <- dlply(df, .(method), function (x1) {     ggplot(subset(melt(cor(x1[sapply(x1,is.numeric)]))[lower.tri(c),],var1 != var2),            aes(x=var1,y=var2,fill=value)) + geom_tile(aes(fill = value),colour = "white") +         geom_text(aes(label = sprintf("%1.2f",value)), vjust = 1) +          theme_bw() +         scale_fill_gradient2(name="r^2",midpoint=0.7,low = "white", high = "red") + xlab(null)+ylab(null) + theme(axis.text.x=element_blank(),axis.text.y=element_blank(), axis.ticks=element_blank(),panel.border=element_blank()) + ggtitle(x1$method) + theme(plot.title = element_text(lineheight=1,face="bold")) + geom_text(data = subset(melt(cor(x1[sapply(x1,is.numeric)])),var1==var2),aes(label=var1),vjust=3 ) })  #function grab legend g_legend<-function(a.gplot){     tmp <- ggplot_gtable(ggplot_build(a.gplot))     leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")     legend <- tmp$grobs[[leg]]     legend }  legend <- g_legend(plots$wig_method)   grid.arrange(legend,plots$single_roi+theme(legend.position='none'), plots$simple_2_roi+theme(legend.position='none'),plots$wig_method+theme(legend.position='none'), plots$wig_drawn_bg+theme(legend.position='none'), ncol=5, nrow=1, widths=c(1/17,4/17,4/17,4/17,4/17)) 

this achieves following plot