Awesome, thanks!
Yes those two numbers on y axis I calculated as (#of EQTLs)/(#of genes) and
the same for the other, RG condition. So implicitly I do have a spread just
that data was not used to plot this, only those ratios. Is in this case
still p value not necessary?
On Fri, 27 Sep 2019 at 23:43, Vivek Das <vd4mm...@gmail.com> wrote:
> Ah, this is a single observation and not pvalue calculation over a
> distribution. You don’t seem to have a spread. Here your code seemed like
> it was over all genes(more than 1) vs RG genes(also more than one). But it
> is basically an observation of difference of 2 values. So it doesn’t need
> to calculate any pvalues. Probability calculation is only needed when you
> have distribution of data in each arm to make Ho(null hypothesis) thar
> ststes condition 1 vs condition 2 have no difference but when you compute
> the distribution, you find a difference that rejects your Null and makes
> the alternative hypotheses true.
>
> Just observed your “prop” is between only two values. So no reason for
> comparing since there is no distribution.
>
> Just make barplot and compute the Delta that can be difference between
> 70.42-7.75 or fold change 70.42/7.75. If they are absolute value you can
> also scale them in log scale and do the same. Hope this helps. Good luck.
>
> Vivek
>
> On Fri, Sep 27, 2019 at 9:32 PM Ana Marija <sokovic.anamar...@gmail.com>
> wrote:
>
>> Hi Vivek,
>>
>> Thanks for getting back to me and yes that is what I tried:
>>
>> library(ggpubr)
>> library(ggplot2)
>> df <- data.frame("prop" = c(7.75,70.42), "Name" = c("All Genes","RG
>> Genes"))
>> my_comparisons <- list(c("All Genes","RG Genes"))
>>
>> p <-ggbarplot(df, x="Name", y="prop",fill="Name",legend ="",color =
>> "white",palette = "jco",xlab = FALSE,ylab="cis eqtl per gene")
>>
>> p + stat_compare_means(comparisons=my_comparisons)
>>
>> I got p value 1, I am wondering does putting here p value makes sense
>> because I don't have any distribution, I just have these two numbers
>> on y axis:
>> "prop" = c(7.75,70.42)
>>
>> Please advise,
>>
>> Thanks
>> Ana
>>
>>
>> On Fri, Sep 27, 2019 at 11:21 PM Vivek Das <vd4mm...@gmail.com> wrote:
>> >
>> > You will need to add stat_compare_means. Take a look at here.
>> >
>> >
>> >
>> http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/76-add-p-values-and-significance-levels-to-ggplots/
>> >
>> > library(ggpubr)
>> > p + stat_compare_means()
>> >
>> > Should be fine.
>> >
>> > Vivek
>> >
>> > On Fri, Sep 27, 2019 at 7:29 PM Ana Marija <sokovic.anamar...@gmail.com>
>> wrote:
>> >>
>> >> Hi,
>> >>
>> >> I created a bar plot with this code:
>> >>
>> >> library(ggplot2)
>> >> df <- data.frame("prop" = c(7.75,70.42), "Name" = c("All Genes","RG
>> Genes"))
>> >> p<-ggplot(data=df, aes(x=Name, y=prop,fill=Name)) +
>> >> geom_bar(stat="identity")+ labs(x="", y = "Proportion of cis
>> >> EQTLs")+ scale_fill_brewer(palette="Greens") +
>> >> theme_minimal()+theme(legend.position = "none")
>> >> p
>> >>
>> >> What do I need to change in my plot so that I have plot with p value
>> >> shown on the attached figure?
>> >>
>> >> Thanks
>> >> 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.
>> >
>> > --
>> > ----------------------------------------------------------
>> >
>> > Vivek Das, PhD
>>
> --
> ----------------------------------------------------------
>
> Vivek Das, PhD
>
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