Change colours of a ggplot object created by a function - r

Question

I am using the fgsea library for some analyses, in particular I use the plotEnrichment function a lot. This function returns a ggplot object with all the layers, but I'd like to change the curve it shows from bright to something else. This code
library(fgsea)
data(examplePathways)
data(exampleRanks)
p = plotEnrichment(examplePathways[["5991130_Programmed_Cell_Death"]], exampleRanks)
will return this plot
Is there any way to change the colour once its created?
Note: I am pretty sure there are ways to do this fairly easily, but I did not create the plot so I don't know what each layer is called or how they were created.
As per BrianFisher's recommendations, I tried
p + scale_color_brewer(palette="GnBu")
p + scale_color_manual(values=c("blue","red"))
But they did not change anything on the plot, as far as I could tell.

Answer 1

Another way to achieve this is by changing the ggplot object directly by using the following code:
## change the aes parameter in the object
p$layers[[5]]$aes_params$colour <- 'blue'
## then plot p
p
This yields the following graph:
A short walk-through
This technique has proven useful to me on numerous occasions. Hence, some more detail:
p$layers gives us the info we need to dig further: we need to access the geom_line configuration. So, after consulting the info below, we choose to continue with p$layers[[5]]
> p$layers
[[1]]
geom_point: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
[[2]]
mapping: yintercept = ~yintercept
geom_hline: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
[[3]]
mapping: yintercept = ~yintercept
geom_hline: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
[[4]]
mapping: yintercept = ~yintercept
geom_hline: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
[[5]]
geom_line: na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
[[6]]
mapping: x = ~x, y = ~-diff/2, xend = ~x, yend = ~diff/2
geom_segment: arrow = NULL, arrow.fill = NULL, lineend = butt, linejoin = round, na.rm = FALSE
stat_identity: na.rm = FALSE
position_identity
If we add an $ after p$layers[[5]], we get the possible choices to extend the code (in RStudio) like in the picture below:
We choose aes_params and add a new $. At that moment, the only choice is colour. We are at the endpoint: here we can set colour of the geom_line.
So, now you know where the hacky, mysterious code came from; and here it is for the very last time:
p$layers[[5]]$aes_params$colour <- 'blue'

Answer 2

If you look at plotEnrichment:
plotEnrichment
function (pathway, stats, gseaParam = 1, ticksSize = 0.2)
{
rnk <- rank(-stats)
ord <- order(rnk)
statsAdj <- stats[ord]
statsAdj <- sign(statsAdj) * (abs(statsAdj)^gseaParam)
statsAdj <- statsAdj/max(abs(statsAdj))
pathway <- unname(as.vector(na.omit(match(pathway, names(statsAdj)))))
pathway <- sort(pathway)
gseaRes <- calcGseaStat(statsAdj, selectedStats = pathway,
returnAllExtremes = TRUE)
bottoms <- gseaRes$bottoms
tops <- gseaRes$tops
n <- length(statsAdj)
xs <- as.vector(rbind(pathway - 1, pathway))
ys <- as.vector(rbind(bottoms, tops))
toPlot <- data.frame(x = c(0, xs, n + 1), y = c(0, ys, 0))
diff <- (max(tops) - min(bottoms))/8
x = y = NULL
g <- ggplot(toPlot, aes(x = x, y = y)) + geom_point(color = "green",
size = 0.1) + geom_hline(yintercept = max(tops), colour = "red",
linetype = "dashed") + geom_hline(yintercept = min(bottoms),
colour = "red", linetype = "dashed") + geom_hline(yintercept = 0,
colour = "black") + geom_line(color = "green") + theme_bw() +
geom_segment(data = data.frame(x = pathway), mapping = aes(x = x,
y = -diff/2, xend = x, yend = diff/2), size = ticksSize) +
theme(panel.border = element_blank(), panel.grid.minor = element_blank()) +
labs(x = "rank", y = "enrichment score")
g
}
The color is hardcoded in geom_line(color = "green"), partly because there is no column in the data.frame that specifies the color. so you have two options:
a) Plot over it
p + geom_line(color="steelblue")
b) change the function and save it as another function (e.g plotEnr below)
plotEnr = function (pathway, stats, gseaParam = 1, ticksSize = 0.2)
{
LINECOL = "red"
rnk <- rank(-stats)
ord <- order(rnk)
statsAdj <- stats[ord]
statsAdj <- sign(statsAdj) * (abs(statsAdj)^gseaParam)
statsAdj <- statsAdj/max(abs(statsAdj))
pathway <- unname(as.vector(na.omit(match(pathway, names(statsAdj)))))
pathway <- sort(pathway)
gseaRes <- calcGseaStat(statsAdj, selectedStats = pathway,
returnAllExtremes = TRUE)
bottoms <- gseaRes$bottoms
tops <- gseaRes$tops
n <- length(statsAdj)
xs <- as.vector(rbind(pathway - 1, pathway))
ys <- as.vector(rbind(bottoms, tops))
toPlot <- data.frame(x = c(0, xs, n + 1), y = c(0, ys, 0))
diff <- (max(tops) - min(bottoms))/8
x = y = NULL
g <- ggplot(toPlot, aes(x = x, y = y)) + geom_point(size = 0.1) +
geom_hline(yintercept = max(tops), colour = "red",
linetype = "dashed") +
geom_hline(yintercept = min(bottoms),
colour = "red", linetype = "dashed") + geom_hline(yintercept = 0,
colour = "black") + geom_line(col=LINECOL) + theme_bw() +
geom_segment(data = data.frame(x = pathway), mapping = aes(x = x,
y = -diff/2, xend = x, yend = diff/2), size = ticksSize) +
theme(panel.border = element_blank(), panel.grid.minor = element_blank()) +
labs(x = "rank", y = "enrichment score")
g
}
plotEnr(examplePathways[["5991130_Programmed_Cell_Death"]], exampleRanks)