Ok. Thank you. karena
On Thu, Sep 15, 2011 at 5:33 PM, Bert Gunter [via R] < ml-node+s789695n3816961...@n4.nabble.com> wrote: > You should post this to the r-sig-mixed-models list, not here. > > -- Bert > > On Thu, Sep 15, 2011 at 1:42 PM, karena <[hidden > email]<http://user/SendEmail.jtp?type=node&node=3816961&i=0>> > wrote: > > > Hi Dear all, > > > > I have some gene expression data samples from different tissue types > > ----------------------------------------------- > > - 120 samples from blood (B) > > - 20 samples from Liver (L) > > - 15 samples from Kidney (K) > > - 6 samples from heart (H) > > ----------------------------------------------- > > All the samples are from different individuals, so there are in total 161 > > > individuals from which the DNA was collected. > > > > For each sample DNA, the expression level of 200 genes were obtained, so > > the > > whole expression data is a 161 x 200 matrix. > > > > The purpose of my project is to interrogate, across the 200 genes, how > many > > of them have an expression level consistent across all the tissue types > > examined, how many of them have an expression level different between any > > > two of the tissue types, how many of them have an expression level unique > > > to > > only one tissue (i.e., gene20 is expressed at a very low level (0.1) in > > Liver, but expressed at the same level (~0.7) across all the other tissue > > > types). > > So my hypotheses are: > > H0: Mean(B)=Mean(L)=Mean(K)=Mean(H) > > H1: Mean(B)âⰠMean(L)=Mean(K)=Mean(H) or > Mean(L)âⰠMean(B)=Mean(K)=Mean(H) or > > Mean(K)âⰠMean(B)=Mean(L)=Mean(H) or > Mean(H)âⰠMean(B)=Mean(K)=Mean(L) > > H2: Mean(B)âⰠMean(L)âⰠMean(K)âⰠMean(H) > > > > In my analysis, the gene expression level is the dependent value (Y), the > > > tissue-type is the fixed effects, the inter-individual variation and the > > batch effects are the random effects. So I was suggested to use the 'lme' > > > function to do the analysis. > > We want to compare the Likelihood ratio between models based on different > > > hypothesis. i.e., if I want to see, for one gene, if the expression > levels > > are all different between any two tissue types, that is to compare H2 to > > H1, > > if the p value corresponding to the > > D_H2H1=likelihoodRatio(H2)-likelihoodRatio(H1) in a chi-square > distribution > > is less than 0.05, then we will say H2 is accepted. > > > > However, my problem is, I don't know how to specify these > parameterizations > > in 'lme' function based H0, H1 and H2, respectively. Can anyone help me > > with > > that? > > > > Thank you very much, > > > > Karena > > > > > > > > -- > > View this message in context: > > > http://r.789695.n4.nabble.com/Questions-on-lme-function-urgent-tp3816741p3816741.html > > Sent from the R help mailing list archive at Nabble.com. > > > > ______________________________________________ > > [hidden email] > > <http://user/SendEmail.jtp?type=node&node=3816961&i=1>mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > > http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html> > > and provide commented, minimal, self-contained, reproducible code. > > > > > -- > "Men by nature long to get on to the ultimate truths, and will often be > impatient with elementary studies or fight shy of them. If it were possible > > to reach the ultimate truths without the elementary studies usually > prefixed > to them, these would not be preparatory studies but superfluous > diversions." > > -- Maimonides (1135-1204) > > Bert Gunter > Genentech Nonclinical Biostatistics > > [[alternative HTML version deleted]] > > > ______________________________________________ > [hidden email] <http://user/SendEmail.jtp?type=node&node=3816961&i=2>mailing > list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html<http://www.r-project.org/posting-guide.html> > and provide commented, minimal, self-contained, reproducible code. > > > ------------------------------ > If you reply to this email, your message will be added to the discussion > below: > > http://r.789695.n4.nabble.com/Questions-on-lme-function-urgent-tp3816741p3816961.html > To unsubscribe from Questions on 'lme' function, urgent!, click > here<http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=3816741&code=ZHIuanpob3VAZ21haWwuY29tfDM4MTY3NDF8MTg4Mjc4MTU4MQ==>. > > -- View this message in context: http://r.789695.n4.nabble.com/Questions-on-lme-function-urgent-tp3816741p3816986.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]]
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