[BioC] Top 10% of genes based on p-value in TopTable

Ovokeraye Achinike-Oduaran ovokeraye at gmail.com
Mon May 7 14:55:31 CEST 2012


Thanks Dan. One more question: I want to plot the no. of genes vs
p-value, so what goes into the aes portion of the command for the
non-p.value axis?


Thanks again.

-Avoks

On Mon, May 7, 2012 at 2:38 PM, Dan Du <tooyoung at gmail.com> wrote:
> Hi Ovokeraye,
>
> if your current approach works fine, just change the first line would
> do,
>
> results$threshold = as.factor(results$P.Value<=quantile(results$P.Value,
> 0.1))
>
> and btw, limma does provide a function volcanoplot to do exactly the
> same thing.
>
> HTH
> Dan
>
> On Mon, 2012-05-07 at 14:15 +0200, Ovokeraye Achinike-Oduaran wrote:
>> Hi all,
>>
>> I'm curious to know how I can get and highlight the top 10% of the
>> genes based on p-values that I get from my limma analysis in a volcano
>> plot.
>>
>> I can get the genes highlighted based on an absolute logFC >2 and a
>> p-value<0.01(code below) but I would like to have an idea of the
>> number of genes in the top 10% based simply on p-values.
>>
>> Any help will be greatly appreciated.
>>
>> Thanks.
>>
>> -Avoks
>>
>> results$threshold = as.factor(abs(results$logFC) > 2 & results$P.Value < 0.01)
>> windows()
>> pdf("VolcanoPlot_GSE25724_9.pdf");
>>
>> g = ggplot(data=results, aes(x=logFC, y=-log10(P.Value), colour=threshold)) +
>>   geom_point(alpha=0.4, size=1.75) +
>>   opts(legend.position = "none") +
>>   xlim(c(-8, 8)) + ylim(c(0, 10)) +
>>   xlab("log2 fold change") + ylab("-log10 p-value")
>> g
>> dev.off()
>>
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>



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