Multiple fill legends for each variable in heat map

Question

I have an input file file1.txt:

V1          V2      Score
rs4939134   SIFT    1
rs4939134   Polyphen2   0
rs4939134   MutationAssessor    -1.75
rs151252290 SIFT    0.101
rs151252290 Polyphen2   0.128
rs151252290 MutationAssessor    1.735
rs12364724  SIFT    0
rs12364724  Polyphen2   0.926
rs12364724  MutationAssessor    1.75
rs34448143  SIFT    0.005
rs34448143  Polyphen2   0.194
rs34448143  MutationAssessor    0.205
rs115694714 SIFT    0.007
rs115694714 Polyphen2   1
rs115694714 MutationAssessor    0.895

And this is my R code to plot this table as a heatmap:

library(ggplot2)

mydata <- read.table("file7.txt", header = FALSE, sep = "\t")
names(mydata) <- c("V1", "V2", "Score") 

ggplot(data = mydata, aes(x = V1, y = V2, fill = Score)) + 
  geom_tile() + 
  geom_text(aes(V1, V2, label = Score), color = "black", size = 3) + 
  scale_fill_continuous(type = "viridis", limits = c(-5.76, 5.37)) + 
  labs(x = "pic1", y = "") + 
  theme_bw()
  theme(panel.border = element_rect(colour = "black"),
        panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(), 
        axis.line = element_line(colour = "black"),
        axis.text = element_text(size = 4))

And this the plot I got:

what I need is for each row (each type in V2) I need to put a legend that represented, so at the end there will be 3 legends, each represent (one for SIFT, second for Polyphen and the third for MutationAssessor) with different range that I can specify.

for example: SIFT from (0,1) and Polyphen from (0,1) and MutationAssessor from (-6,6)

I tried different thing of previous asked questions but nothing work with me.

I appreciate any help.

I don't know if it's possible to create legends for more than 2 variables in heat maps. Simple workaround is just to create three different plots. — pogibas, Sep 12 '18 at 11:51
No I need to be as a one plot in order to compare, it's really better than separating them into different plots @PoGibas — LamaMo, Sep 12 '18 at 11:53

pogibas · Accepted Answer · 2018-09-12T12:26:16.120

You can loop over three given variables and plot different plots for each of them. In the end you have to combine them.

Create dataset with wanted limits:

myLimits <- list(
    list("SIFT", 0, 1),
    list("Polyphen2", 0, 1),
    list("MutationAssessor", -6, 6)
)

Function to plot heatmap only for one variable at a time:

plotHeat <- function(type, MIN, MAX) {
    library(ggplot2)
    p <- ggplot(subset(mydata, V2 == type), 
                aes(V1, V2, fill = Score, label = Score)) + 
        geom_tile() + 
        geom_text(color = "black", size = 3) + 
        scale_fill_continuous(type = "viridis", limits = c(MIN, MAX)) + 
        labs(x    = "SNP", 
             y    = NULL,
             fill = type) + 
        theme_bw()
    # Output x-axis only for the last plot
    if (type != myLimits[[length(myLimits)]][[1]]) {
        p <- p + theme(axis.text.x = element_blank(),
                       axis.title.x = element_blank(),
                       axis.line.x = element_blank(),
                       axis.ticks.x = element_blank())
    }
    return(p)
}

Plot and combine plots using egg package:

res <- lapply(myLimits, function(x) {plotHeat(x[[1]], x[[2]], x[[3]])})
egg::ggarrange(plots = res)

Wow I like it :))), thanks a lot 3 plots but they looks as a one, thanks again — LamaMo, Sep 12 '18 at 12:37

Adela · Answer 2 · 2018-09-12T12:44:32.043

This is maybe related to this.

xs <- split(mydata, f = mydata$V2)

p1 <- ggplot(data = xs$MutationAssessor, aes(x = V1, y = 0, fill = Score)) + 
  geom_tile() + 
  geom_text(aes(label = Score), color = "black", size = 3) + 
  scale_fill_continuous(type = "viridis", limits = c(-5.76, 5.37)) + 
  labs(x = "pic1", y = "") + 
  facet_grid(V2 ~ .) + 
  theme_bw() + 
  theme(panel.border = element_rect(colour = "black"), 
        panel.grid.major = element_blank(),   
        panel.grid.minor = element_blank(), 
        axis.line = element_line(colour = "black"),
        axis.text = element_text(size = 4))

p2 <- p1 %+% xs$Polyphen2
p3 <- p1 %+% xs$SIFT

library(gridExtra)
grid.arrange(p1, p2, p3)

And the result is:

EDIT:

In case you want different range for facets but you want values to be comparable (e.g. value around 5 should be yellow in all plots), there is a possible solution

First discretize your fill variable

mydata$colour <- cut(mydata$Score, 
                     quantile(mydata$Score, c(0, 0.25, 0.5, 0.75, 1)), 
                     include.lowest = T)

Then create plots:

xs <- split(mydata, f = mydata$V2)

p1 <- ggplot(data = xs$MutationAssessor, aes(x = V1, y = 0, fill = colour)) + 
  geom_tile() + 
  geom_text(aes(label = Score), color = "black", size = 3) + 
  labs(x = "pic1", y = "") + 
  facet_grid(V2 ~ .) + 
  theme_bw() + 
  theme(panel.border = element_rect(colour = "black"), 
        panel.grid.major = element_blank(),   
        panel.grid.minor = element_blank(), 
        axis.line = element_line(colour = "black"),
        axis.text = element_text(size = 4))

p2 <- p1 %+% xs$Polyphen2
p3 <- p1 %+% xs$SIFT

And finally change palette:

mypalette <- c("#FFFFCC", "#A1DAB4", "#41B6C4", "#2C7FB8", "#253494")
names(mypalette) <- levels(mydata$colour)

p1 <- p1 + scale_fill_manual(values = mypalette[levels(xs$MutationAssessor$colour)]) 
p2 <- p2 + scale_fill_manual(values = mypalette[levels(xs$Polyphen2$colour)]) 
p3 <- p3 + scale_fill_manual(values = mypalette[levels(xs$SIFT$colour)])

And the result is:

grid.arrange(p1, p2, p3)

But the legend values range I wanted to be different in each type, as I mentioned in the question. SIFT from (0,1) and Polyphen from (0,1) and MutationAssessor from (-6,6) — LamaMo, Sep 12 '18 at 12:07

Multiple fill legends for each variable in heat map

2 Answers2

EDIT: