Venn Diagrams in Limma
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Jason Skelton ▴ 510
@jason-skelton-135
Last seen 10.3 years ago
Hi All............... I have a couple of questions about the venn diagrams options in Limma 1) Once you have obtained your venn diagram how can you "identify" or make lists of genes from the different venn components ? 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 ? I've searched the Bioconductor mailing list but can't find any info on this. Thanks 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
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@gordon-smyth
Last seen 16 hours ago
WEHI, Melbourne, Australia
At 04:14 AM 28/10/2003, Jason Skelton wrote: >I have a couple of questions about the venn diagrams options in Limma > >1) >Once you have obtained your venn diagram how can you "identify" or make >lists of genes from the different venn components ? 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. >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(). Gordon >I've searched the Bioconductor mailing list but can't find any info on this. > >Thanks > >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 > >_______________________________________________ >Bioconductor mailing list >Bioconductor@stat.math.ethz.ch >https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor
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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
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At 10:23 PM 28/10/2003, Jason Skelton wrote: >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) Go one step back, to the classification matrix which comes out of classifyTests(). That gives you a classification matrix with one row for each gene in the uniquegenelist. >>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) No there isn't. imageplot truncates names to 15 characters. You would have to modify the code yourself to change that. >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 Use heatDiagram() instead. That function will accept a classification matrix from classifyTestsP which will allow you to specify your desired p-value cutoff. Gordon >Thanks for you help > >Jason
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