Hello, unfortunately I have I big problem I can't solve. I have to analyze if a gene is tissue specific. For example for the gene xyz I have following expression values: Heart Liver Brain ....several others 8.998497 10.013561 12.277407 9.743556 10.137574 11.033957 For every tissue I have two values from two different experiments. Now I want to test if Heart is significant higher than Liver and Brain, or Liver is significant higher than Heart an Brain, ... I read about the pairwise.t.test, but I dont't want to test Heart against Liver and Heart against Brain, ... Is there any possibility to do that? ANOVA? Duncan? Constrasts? When I set up a contrasts matrix like Heart Liver Brain C1 1 -1/2 -1/2 C2 -1/2 1 -1/2 C3 -1/2 -1/2 1 to get tissue specific genes, some p-values are exact 0 (even I corrected with holm). This can't be correct? Are only degree of freedoms times contrasts allowed? Please help ____________________________________________________________________ Ihre Messenger, Communities und E-Mails jetzt in einem Programm!

Hi Pascal, You could always look at modifying a chi-square test so that a given gene is classified as being tissue specific if it's value in one tissue is over the expected value? You can have a look at this paper to see if it is of any help: Genet. Sel. Evol. 38 (2006) 321-341 Cheers, Sean On 7/15/08 3:42 AM, "Pascal Gellert" <pascal_g at="" web.de=""> wrote: > Hello, > > unfortunately I have I big problem I can't solve. > > I have to analyze if a gene is tissue specific. For example for the gene xyz I > have following expression values: > > Heart Liver Brain ....several others > 8.998497 10.013561 12.277407 > 9.743556 10.137574 11.033957 > > For every tissue I have two values from two different experiments. > > Now I want to test if Heart is significant higher than Liver and Brain, or > Liver is significant higher than Heart an Brain, ... > > I read about the pairwise.t.test, but I dont't want to test Heart against > Liver and Heart against Brain, ... > > Is there any possibility to do that? ANOVA? Duncan? Constrasts? > > When I set up a contrasts matrix like > > Heart Liver Brain > C1 1 -1/2 -1/2 > C2 -1/2 1 -1/2 > C3 -1/2 -1/2 1 > > to get tissue specific genes, some p-values are exact 0 (even I corrected with > holm). This can't be correct? Are only degree of freedoms times contrasts > allowed? > > > Please help > ____________________________________________________________________ > Ihre Messenger, Communities und E-Mails jetzt in einem Programm! > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor

On Jul 15, 2008, at 12:42 AM, Pascal Gellert wrote: > Hello, > > unfortunately I have I big problem I can't solve. > > I have to analyze if a gene is tissue specific. For example for the > gene xyz I have following expression values: > > Heart Liver Brain ....several others > 8.998497 10.013561 12.277407 > 9.743556 10.137574 11.033957 > > For every tissue I have two values from two different experiments. > > Now I want to test if Heart is significant higher than Liver and > Brain, or Liver is significant higher than Heart an Brain, ... > > I read about the pairwise.t.test, but I dont't want to test Heart > against Liver and Heart against Brain, ... > > Is there any possibility to do that? ANOVA? Duncan? Constrasts? > > When I set up a contrasts matrix like > > Heart Liver Brain > C1 1 -1/2 -1/2 > C2 -1/2 1 -1/2 > C3 -1/2 -1/2 1 > > to get tissue specific genes, some p-values are exact 0 (even I > corrected with holm). This can't be correct? Are only degree of > freedoms times contrasts allowed? Whether or not this contrast matrix makes sense depends on your design matrix. Given your p-values I would guess you are doing something wrong, but I have no idea what. There could also be some problems with your data but again it is hard to tell you what is wrong. Take a look at the raw data for some of the genes with a p-value of zero, perhaps you can learn something. Kasper

Perhaps these 2 papers can be useful for you, http://genomebiology.com/2005/6/4/R33 http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1501047 Regards, Jose -- -------------------------------------- ALTERNATIVE EMAIL: josem.muinyo at cmb.udl.es Jose M Muino Institute of Plant Genetics Polish Academy of Science Strzeszynska 34 60-479 Poznan Poland tel. 48 61 6550254

Hello Jose, actually this could be a good idea. I heard about Shannon entropy, so I'll try this soon. Pascal

Hello Sean, thank you for your answer. I tried to do this with ANOVA. Each gene against all other genes for every tissue. Unfortunately the p-values are sometimes >> 0.05 even the gene should be classified as tissue specific.