[BioC] Venn Diagrams in Limma
Jason Skelton
jps at sanger.ac.uk
Tue Oct 28 12:23:05 MET 2003
Hi Gordon
Gordon Smyth wrote:
> Venn diagrams are by their nature simply overall counts. But you can
> easily identify the relevant genes from the 'classification' object
> from which the Venn diagram is computed.
Not sure how this is done, the object I have created in ClassifyTests
has classification (0 and 1's) and Fstats associated with it
am I looking in the wrong place ? I have a list of genes made from
uniquegenelist is this the list I'm wanting to access ?
My VennCounts object is:
DIF1 DIF2 DIF3 Counts
[1,] 0 0 0 1925
[2,] 0 0 1 18
[3,] 0 1 0 26
[4,] 0 1 1 5
[5,] 1 0 0 70
[6,] 1 0 1 13
[7,] 1 1 0 90
[8,] 1 1 1 59
attr(,"class")
[1] "VennCounts"
could you give an example of how to associate each of the 8 counts with
genes from the uniquegenelist (OR other)
2)
I'd also like to be able to use the false discovery rate option that can
beused in classifyTestsP method for my venn diagram but I also want to
use data that I've received from makeContrasts and contrast.fit which I
can only use in classifyTests but I can't use "fdr" in that function....
Is there a particular reason why I can't do this ?
Yes there is. classifyTests() uses a method intended to control false
discovery rate across contrasts. This is not compatible with the simple
p.adjust() approach to controling FDR across genes. I suggest that you
simply find what unadjusted p-value corresponds to your desired FDR
level and enter that to classifyTests().
OK that makes more sense now thanks.
I have yet more questions about the heatdiagram option
My gene names are very long 28+ characters long is there a heatdiagram
specific command that alters the size of the box that the heatmap covers ?
So that genes appearing on the plot are not truncated (I've tried some
of the R commands for Margins etc but they don't want to work with high
level plots)
Also in the heatdiagram you can specify EB$t and fit$coef
e.g. heatdiagram(newDIF123SEPcontrastfitEB$t,
newDIF123SEPcontrastsfit$coef etc)
you can specify the critical.primary argument which is the critical
value "above" which genes are considered significant.
BUT
If you want to use EB$p.value fit$coef
e.g. heatdiagram(newDIF123SEPcontrastfitEB$p.value,
newDIF123SEPcontrastsfit$coef etc)
you can't specify the critical.primary because you need to specify a
maximum value e.g(0.05) rather than minimum as your cutoff
Thanks for you help
Jason
--------------------------------
Jason Skelton
Pathogen Microarrays
Wellcome Trust Sanger Institute
Hinxton
Cambridge
CB10 1SA
Tel +44(0)1223 834244 Ext 7123
Fax +44(0)1223 494919
More information about the Bioconductor
mailing list