including p-value gradient in stacked bar plot

Question

I have input which looks like the following :

Sample input

Pathways    Genecount_T1    fold Enrichment_T1  P-value_T1  Genecount_T2    fold Enrichment_T1  P-value_T2
Ubiquitin proteasome pathway (P00060)   44  3.04    4.87E-08    43  2.78    1.01E-06
p38 MAPK pathway (P05918)   22  2.47    2.35E-02    24  2.52    8.94E-03
Ras Pathway (P04393)    37  2.27    1.06E-03    38  2.18    1.92E-03
PDGF signaling pathway (P00047) 64  1.99    6.40E-05    70  2.04    8.26E-06

I have to build a stacked barplot from the columns as shown in figure 2.I need to include a color bar that shows p-values in the bars instead of solid colors as shown in figure 1.

How to do it using R ?

Hi @shome! Can you paste the output from `dput(your_data)` here? It would be easier to copy your data and replicate your problem. Please check [how to ask a good R question](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) — patL, Nov 02 '19 at 13:15

score 2 · Accepted Answer · answered Nov 02 '19 at 19:03

library(ggplot2)
# your table
tab <- structure(list(Pathways = c("Ubiquitin proteasome pathway (P00060)", 
"p38 MAPK pathway (P05918)", "Ras Pathway (P04393)", "PDGF signaling pathway (P00047)"
), Genecount_T1 = c(44L, 22L, 37L, 64L), fold.Enrichment_T1 = c(3.04, 
2.47, 2.27, 1.99), P.value_T1 = c(4.87e-08, 0.0235, 0.00106, 
6.4e-05), Genecount_T2 = c(43L, 24L, 38L, 70L), fold.Enrichment_T2 = c(2.78, 
2.52, 2.18, 2.04), P.value_T2 = c(1.01e-06, 0.00894, 0.00192, 
8.26e-06)), class = "data.frame", row.names = c(NA, -4L))

# very crude way to put data into long format

COLS = c("Pathways","Genecount","fold.Enrichment","P.value")
df1 = data.frame(tab[,1:4])
colnames(df1) = COLS
df1$grp = "T1"
df2 = data.frame(tab[,c(1,5:7)])
colnames(df2) = COLS
df2$grp = "T2"
df = rbind(df1,df2)

you can look at the long format:

head(df)

                               Pathways Genecount fold.Enrichment  P.value grp
1 Ubiquitin proteasome pathway (P00060)        44            3.04 4.87e-08  T1
2             p38 MAPK pathway (P05918)        22            2.47 2.35e-02  T1
3                  Ras Pathway (P04393)        37            2.27 1.06e-03  T1
4       PDGF signaling pathway (P00047)        64            1.99 6.40e-05  T1
5 Ubiquitin proteasome pathway (P00060)        43            2.78 1.01e-06  T2
6             p38 MAPK pathway (P05918)        24            2.52 8.94e-03  T2

Now we plot it with ggplot, note that the color bar is log10 transformed:

ggplot(df,aes(x=Pathways,y=Genecount,fill=-log10(P.value),group=grp)) + 
geom_col(position="dodge",width=0.4,size=0.7) +
 coord_flip() + scale_fill_viridis(trans='log10',option="B")

In your question, I guess you wanted a combination of the side-by-side and gradient barplot, but how do you distinguish the two groups now? Not very easy to shade by different fill gradients or add texture. I have two suggestions below:

ggplot(df,aes(x=Pathways,y=Genecount,linetype=grp,fill=-log10(P.value),group=grp)) + 
geom_col(position="dodge",width=0.4,size=0.7,col="black") +
 coord_flip() + scale_fill_viridis(trans='log10',option="B")

or facet:

ggplot(df,aes(x=grp,y=Genecount,fill=-log10(P.value))) + 
geom_col(position="dodge",width=0.4) +
coord_flip() + scale_fill_viridis(trans='log10',option="B")+
facet_grid(Pathways~.)+
theme(strip.text.y = element_text(angle = 0))

including p-value gradient in stacked bar plot

1 Answers1