Hi Ana,
Okay, it's the lattice package. Try this:
panel.abline(v=-4)
panel.text(-3.9,0.35,"*")
As I don't have your data I can't provide a complete example.
Jim
On Wed, Feb 12, 2020 at 8:50 AM Ana Marija <sokovic.anamar...@gmail.com> wrote:
>
> Hi Jim
>
>
> I tried your code and it didn't show me density curves.
>
> However I was able to do teh plot myself via:
>
> densityplot(~dat,data=tot,
> groups=type,
> par.settings = list(superpose.line = list(col = c("blue","red"))),
> xlab="log2 (variance)",
> plot.points=FALSE,
> auto.key=TRUE)
>
>
> and it is attached. The only thing I need to do is to make a line in
> between peaks of the curves and put the star above that line. Not a p
> value but just a star symbol.
>
> Please advise,
> Thanks
>
> On Tue, Feb 11, 2020 at 3:46 PM Ana Marija <sokovic.anamar...@gmail.com>
> wrote:
> >
> > Hi Jim
> >
> >
> > I tried your code and it didn't show me density curves.
> >
> > However I was able to do teh plot myself via:
> >
> > densityplot(~dat,data=tot,
> > groups=type,
> > par.settings = list(superpose.line = list(col = c("blue","red"))),
> > xlab="log2 (variance)",
> > plot.points=FALSE,
> > auto.key=TRUE)
> >
> >
> > and it is attached. The only thing I need to do is to make a line in
> > between peaks of the curves and put the star above that line. Not a p
> > value but just a star symbol.
> >
> > Please advise,
> > Thanks
> > Ana
> >
> > On Tue, Feb 11, 2020 at 3:23 PM Jim Lemon <drjimle...@gmail.com> wrote:
> > >
> > > Hi Ana,
> > > Your image didn't make it through (as usual). Try PNG or PDF format.
> > >
> > > Assumptions
> > > 1) You want to plot two lines using the _paired_ values of inter- and
> > > intra-individual variance.
> > > 2) The cases are in the same order in your data
> > > 3) You want to identify the two lines
> > > 4) You want to place text with some p-value between the lines
> > >
> > > This is really (and suspiciously) simple. Here's a start:
> > >
> > > tot<-read.table(text="dat type
> > > -3.962 inter.individual.variance
> > > -4.301 inter.individual.variance
> > > -1.690 inter.individual.variance
> > > -0.375 inter.individual.variance
> > > 1.816 inter.individual.variance
> > > 0.138 inter.individual.variance
> > > -4.09 intra.individual.variance
> > > -4.64 intra.individual.variance
> > > -5.57 intra.individual.variance
> > > -2.96 intra.individual.variance
> > > -4.43 intra.individual.variance
> > > -3.60 intra.individual.variance",
> > > header=TRUE)
> > > # get the numeric values of the factor 'type'
> > > tot$ntype<-as.numeric(tot$type)
> > > plot(tot$dat[tot$ntype==1],type="l",col="green",ylim=range(tot$dat))
> > > lines(tot$dat[tot$ntype==2],col="blue")
> > > text(5,-1.5,"p = 0.005")
> > > legend(1,1,c("Inter-individual variance","Intra-individual variance"),
> > > lty=1,col=c("green","blue"))
> > >
> > > Jim
> > >
> > > On Wed, Feb 12, 2020 at 7:07 AM Ana Marija <sokovic.anamar...@gmail.com>
> > > wrote:
> > > >
> > > > so I transformed my data from the previous email to look like this:
> > > >
> > > > > head(tot)
> > > > dat type
> > > > 1 -3.962 inter.individual.variance
> > > > 2 -4.301 inter.individual.variance
> > > > 3 -1.690 inter.individual.variance
> > > > 4 -0.375 inter.individual.variance
> > > > 5 1.816 inter.individual.variance
> > > > 6 0.138 inter.individual.variance
> > > > > tail(tot)
> > > > dat type
> > > > 31177 -4.09 intra.individual.variance
> > > > 31178 -4.64 intra.individual.variance
> > > > 31179 -5.57 intra.individual.variance
> > > > 31180 -2.96 intra.individual.variance
> > > > 31181 -4.43 intra.individual.variance
> > > > 31182 -3.60 intra.individual.variance
> > > >
> > > > then I can make plot using this:
> > > >
> > > > densityplot(~dat,data=tot,
> > > > groups=type,
> > > > par.settings = list(superpose.line = list(col =
> > > > c("blue","red"))),
> > > > xlab="log2 (variance)",
> > > > plot.points=FALSE,
> > > > auto.key=TRUE)
> > > >
> > > > and calculate my p value with t test, say it is 0.005
> > > >
> > > > But how to add that p value in between distribution of the curves?
> > > >
> > > > Thanks
> > > > Ana
> > > >
> > > > On Tue, Feb 11, 2020 at 12:54 PM Ana Marija
> > > > <sokovic.anamar...@gmail.com> wrote:
> > > > >
> > > > > Hi,
> > > > >
> > > > > I have data like this:
> > > > >
> > > > > > head(a)
> > > > > X geneID inter.individual.variance
> > > > > intra.individual.variance F.value p.value CV
> > > > > 1 3iUZ.47hLFki49VR4o MLLT10 0.0642
> > > > > 0.01395 4.60 1.00e-05 0.0222
> > > > > 2 fEn1QlU0MCVe9GeR64 C1orf123 0.0507
> > > > > 0.00671 7.57 1.00e-08 0.0172
> > > > > 3 ud_tTlU5LtB478JxIk FSD1L 0.3100
> > > > > 0.02682 11.56 1.00e-11 0.0639
> > > > > 4 3KV3OJIIRuJ5KJ6VkI TXNDC11 0.7710
> > > > > 0.02813 27.41 9.99e-19 0.0688
> > > > > 5 o_rupcEAKnQqnoh6ec CYB5R2 3.5209
> > > > > 0.03391 103.83 9.99e-31 0.1357
> > > > > 6 Nk_t6ULcQ7VDNChBRU GBP1 1.1005
> > > > > 0.09522 11.56 9.98e-12 0.0773
> > > > >
> > > > > I would like to create density plot, like the attached between
> > > > > "inter.individual.variance" and "intra.individual.variance" and have p
> > > > > value between those two curves.
> > > > >
> > > > > Please advise,
> > > > > Ana
> > > >
> > > > ______________________________________________
> > > > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see
> > > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > > PLEASE do read the posting guide
> > > > http://www.R-project.org/posting-guide.html
> > > > and provide commented, minimal, self-contained, reproducible code.
______________________________________________
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