Two scatterplots with groups and a trendline
Ace
experimentvalue(cat/dog)). 2 have 2 columns (name, group).
My goal is 2 scatterplots arranged next to each other with a trendline
each and the points colored differently by group. Here is my code.
info <- read.csv(file.choose())
info2<-read.csv(file.choose())
responseCATS<-read.csv(file.choose())
responseDOGS<-read.csv(file.choose())
library(ggplot2)
library(grid)
infomerge <- merge(info, responseCATS, by="name")
infomerge2 <- merge(info2, responseDOGS, by="name")
df = data.frame(siControl =infomerge$value_siCONTROL, siCATS=infomerge
$value_siCATS, namelab=infomerge$name, Group=infomerge$Group)
df2 = data.frame(siControl =infomerge2$value_siCONTROL,
siDOGS=infomerge2$value_siDOGS,
namelab=infomerge2$name,Group=infomerge2$Group )
plot1 <- ggplot(df, aes(x=siControl, y=siCATS, colour=Group)) +
geom_point()+ geom_smooth(method="lm")
plot2 <- ggplot(df2, aes(x=siControl, y=siDOGS, colour=Group)) +
geom_point()+ geom_smooth(method="lm")
vp.layout <- function(x, y) viewport(layout.pos.row=x,
layout.pos.col=y)
arrange <- function(..., nrow=NULL, ncol=NULL, as.table=FALSE) {
dots <- list(...)
n <- length(dots)
if(is.null(nrow) & is.null(ncol)) { nrow = floor(n/2) ; ncol =
ceiling(n/nrow)}
if(is.null(nrow)) { nrow = ceiling(n/ncol)}
if(is.null(ncol)) { ncol = ceiling(n/nrow)}
## NOTE see n2mfrow in grDevices for possible alternative
grid.newpage()
pushViewport(viewport(layout=grid.layout(nrow,ncol) ) )
ii.p <- 1
for(ii.row in seq(1, nrow)){
ii.table.row <- ii.row
if(as.table) {ii.table.row <- nrow - ii.table.row + 1}
for(ii.col in seq(1, ncol)){
ii.table <- ii.p
if(ii.p > n) break
print(dots[[ii.table]], vp=vp.layout(ii.table.row, ii.col))
ii.p <- ii.p + 1
}
}
}
arrange(plot1,plot2,ncol=1)
The problem is that instead of one trendline per graph I'm getting
several. Also it seems that only a few points are showing up on the
graph instead of all of them. Is there any other thing wrong with the
code that you can see? Thanks
Brandon Hurr
geom_point(df, aes(x=siControl, y=siCATS, colour=Group)) +
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Ace
On Apr 8, 1:59 am, Brandon Hurr <brandon.h...@gmail.com> wrote:
> You're doing a lot of stuff here and some of it looks unnecessary, but it's
> hard to tell without the original data. Could you please provide sample
> datasets or dput(df) and dput(df2)?
>
> It seems to me that you could rbind() df and df2 together and use faceting
> to get your side-by-side plots so you don't need to use the viewports.
>
> The reason why you're getting multiple lines per plot is that your
> geom_smooth() is inheriting colour=Group from your ggplot() call. At least
> that is my theory in the absence of data. A way around this would be...
>
> plot1 <- ggplot() +
> geom_point(df, aes(x=siControl, y=siCATS, colour=Group)) +
> geom_smooth(df, aes(x=siControl, y=siCATS), method="lm")
>
> And the same for plot2...
>
> Brandon
>
with data of class uneval'
I'm also trying to add point labels to the graph but it isn't working
either
plot1 <- ggplot() + geom_point(df, aes(x=siControl, y=siCATS,
label=name))+ geom_smooth(df, aes(x=siControl, y=siCATS),
method="lm")
Sample data would be
info (3 columns Name siControl and siCATS)
Name siControl siCATS
Point1 0 3
Point2 1 1
Point3 2 3
Point4 3 2
ResponseCATS (2 Columns Name and Group)
Name Group
Point1 1
Point2 1
Point3 2
Point4 2
Brandon Hurr
ggplot(data=infomerge, aes(x=siControl, y=siCATS)) + geom_point(aes(colour=as.factor(group))) + geom_text(aes(label=Name), size=2)+ geom_smooth(method="lm")
Previously it was treating "Group" as a numeric and giving a scale, but if they are factors (and I think they are) then using as.factor() is what you need. You'll have to clean up the legend, but I think that's what you're after. 1 smooth line for all the data, different colors for the points, and labels for the points.
A D
properly but I've attached a larger alternate dataset.
>
> I'm not sure if I got there in the end or not, but this is what I got to.
>
> infomerge<-structure(list(Name = structure(1:4, .Label = c("Point1",
> "Point2", "Point3", "Point4"), class = "factor"), siControl = 0:3, siCATS =
> c(3L, 1L, 3L, 2L), group = c(1L, 1L, 2L, 2L)), .Names = c("Name",
> "siControl", "siCATS", "group"), row.names = c(NA, -4L), class =
> "data.frame")
Yes, you have the right idea of what I'm aiming for but I don't
understand what the above is for. I simply used the second part of
your solution.
geneexp <- read.csv(file.choose())
responseTCF7L2<-read.csv(file.choose())
geneexpmerge <- merge(geneexp, responseTCF7L2, by="gene")
df = data.frame(siControl =geneexpmerge$value_siCONTROL,
siTCF7L2=geneexpmerge$value_siTCF7L2, genelab=geneexpmerge$gene,
Group=geneexpmerge$Group)
ggplot(data=df, aes(x=siControl, y=siTCF7L2)) +
geom_smooth(method="lm" ) + coord_trans(x = "log", y = "log") +
geom_point(aes(colour=as.factor(Group))) +
geom_text(aes(label=genelab), size=2)
and it got me mostly what I want except the trendline bends and
doesn't look like its going through the points. I've tried different
things but its either use regular scale and have the points crammed
together or use log and have the bendy trendline.
