CAMERA for non-directional gene sets
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@simon-de-bernard-5481
Last seen 7.9 years ago
The publication for CAMERA (http://nar.oxfordjournals.org/content/earl y/2012/05/24/nar.gks461.full) mentions using the average absolute- logFC as a statistics for "non-directional" gene sets. This would seem like the appropriate approach for gene sets from e.g. the GO database. However I was unable to find how to use anything other than logFC or its rank from the camera documentation in limma. Have I missed something? Thanking you in advance, Best regards, Simon.
GO limma CAMERA GO limma CAMERA • 1.6k views
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Wu, Di ▴ 120
@wu-di-4945
Last seen 7.1 years ago
United States
Hi Simon, Thank you for your interest in using CAMERA. It has lots of good feathers, holding correct false positive rate and having good power. It can be used when you have multiple gene sets, e.g., GO as you mentioned. Currently, the default test statistics for individual genes is the moderated t, which is a variant of the ordinary t. See Smyth 2004. (http://www.statsci.org/smyth/pubs/ebayes.pdf) It is up to the user whether ranks (of the moderated t) should be used or not. Of course, it is easily to edit the code to allow log fold change to represent the change of the individual genes. What other statistics for individual genes will you be interested in using? It is also worth noting that, according to other users, it is safe to set ?allow.neg.cor=FLASE?, to let correlation be zero when the actual calculated correlation is negative. Gordon may also have some insight regarding your question. Enjoy using CAMERA. Di ---- Di Wu Postdoctoral fellow Harvard University, Statistics Department Harvard Medical School Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA ________________________________________ From: bioconductor-bounces@r-project.org [bioconductor- bounces@r-project.org] On Behalf Of Simon de Bernard [simon.debernard@altrabio.com] Sent: Monday, September 03, 2012 6:58 AM To: bioconductor at r-project.org Subject: [BioC] CAMERA for non-directional gene sets The publication for CAMERA (http://nar.oxfordjournals.org/content/earl y/2012/05/24/nar.gks461.full) mentions using the average absolute- logFC as a statistics for "non-directional" gene sets. This would seem like the appropriate approach for gene sets from e.g. the GO database. However I was unable to find how to use anything other than logFC or its rank from the camera documentation in limma. Have I missed something? Thanking you in advance, Best regards, Simon. _______________________________________________ Bioconductor mailing list Bioconductor at r-project.org https://stat.ethz.ch/mailman/listinfo/bioconductor Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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Dear Di, thanks for your answer. > Thank you for your interest in using CAMERA. It has lots of good feathers, holding correct false positive rate and having good power. That's why it piqued my interest ;-) > It can be used when you have multiple gene sets, e.g., GO as you mentioned. > > Currently, the default test statistics for individual genes is the moderated t, which is a variant of the ordinary t. See Smyth 2004. (http://www.statsci.org/smyth/pubs/ebayes.pdf) > > It is up to the user whether ranks (of the moderated t) should be used or not. > > Of course, it is easily to edit the code to allow log fold change to represent the change of the individual genes. What other statistics for individual genes will you be interested in using? Sorry for mixing up logFC and moderated t. However, isn't it still an approach only appropriate for "directional" gene sets? Suppose I have a gene set for which I know that genes should be differentially expressed but not necessarily in the same direction. If half the genes in my set have a statistic of -10 and the other half of +10, won't the current implementation give me p=1 when I would expect significance? Best regards, Simon. > It is also worth noting that, according to other users, it is safe to set ?allow.neg.cor=FLASE?, to let correlation be zero when the actual calculated correlation is negative. > > Gordon may also have some insight regarding your question. > > Enjoy using CAMERA. > > Di > > > > > ---- > Di Wu > Postdoctoral fellow > Harvard University, Statistics Department > Harvard Medical School > Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA
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Wu, Di ▴ 120
@wu-di-4945
Last seen 7.1 years ago
United States
Dear Simon, CAMERA outputs the testing p values with the directions, up, down and either. In your example, you are right that CAMERA gives very large p value to indicate non-significant. It doesn't output the non-directional p value (we also call the non diretional test as the test for the "mixed" direction), as we found the correlation effects in the test for the mixed direction is quite complicated. CAMERA is a competitive gene set test as you may know the major two types are competitive and self-contained. (see Goeman, J. J. and B?uhlmann, P. (2007), and the CAMERA paper). Generally, to test a mixed direction for a competitive hypothesis , Wilcoxon mean rank gene set test (wilcoxGST in limma) can be used although this method ignores gene-gene correlations. According to my experience, the correlation effect in the test of the mixed direction is much weaker than in the directional tests. Another self-contained test ROAST can also be used to help understanding the test for the non-directional tests. (http://bioinformatics.oxfordjournals.org/content/early/2010/07/07/bio informatics.btq401.full.pdf) Hope this help. Di ---- Di Wu Postdoctoral fellow Harvard University, Statistics Department Harvard Medical School Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA ________________________________________ From: Simon de Bernard [simon.debernard@altrabio.com] Sent: Tuesday, September 04, 2012 12:06 PM To: Wu, Di Cc: bioconductor at r-project.org Subject: Re: [BioC] CAMERA for non-directional gene sets Dear Di, thanks for your answer. > Thank you for your interest in using CAMERA. It has lots of good feathers, holding correct false positive rate and having good power. That's why it piqued my interest ;-) > It can be used when you have multiple gene sets, e.g., GO as you mentioned. > > Currently, the default test statistics for individual genes is the moderated t, which is a variant of the ordinary t. See Smyth 2004. (http://www.statsci.org/smyth/pubs/ebayes.pdf) > > It is up to the user whether ranks (of the moderated t) should be used or not. > > Of course, it is easily to edit the code to allow log fold change to represent the change of the individual genes. What other statistics for individual genes will you be interested in using? Sorry for mixing up logFC and moderated t. However, isn't it still an approach only appropriate for "directional" gene sets? Suppose I have a gene set for which I know that genes should be differentially expressed but not necessarily in the same direction. If half the genes in my set have a statistic of -10 and the other half of +10, won't the current implementation give me p=1 when I would expect significance? Best regards, Simon. > It is also worth noting that, according to other users, it is safe to set ?allow.neg.cor=FLASE?, to let correlation be zero when the actual calculated correlation is negative. > > Gordon may also have some insight regarding your question. > > Enjoy using CAMERA. > > Di > > > > > ---- > Di Wu > Postdoctoral fellow > Harvard University, Statistics Department > Harvard Medical School > Science Center, 1 Oxford Street, Cambridge, MA 02138-2901 USA
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