[R] how to create density plot in R with p value

[Jim Lemon]

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.anamarija using 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.anamarija using 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 <drjimlemon using 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.anamarija using 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.anamarija using 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
> > > >
> > > > ______________________________________________
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