Awesome, thanks! Great minds discuss ideas. Average minds discuss events. Small minds discuss people. -Eleanor Roosevelt ________________________________________ From: seandavi@gmail.com [seandavi@gmail.com] on behalf of Sean Davis [sdavis2@mail.nih.gov] Sent: Tuesday, May 07, 2013 5:30 PM To: Johnson, Franklin Theodore Cc: FRANKLIN JOHNSON [guest]; bioconductor at r-project.org; franklin.johnson at wsu.edu Subject: Re: [BioC] No $df.residual On Tue, May 7, 2013 at 8:16 PM, Johnson, Franklin Theodore <franklin.johnson at="" email.wsu.edu=""> wrote: > Dear Sean Davis, > > Thanks for the input. > > I took the average of the RMA normalized values for each genotype. Then, log2 transformed as below: > > The raw data is from NimbleGen array custom-designed for apple genome. > It was normalized using RMA method. This was downloaded from NCBI/GEO, > then I took log2(exprs(eset), after reading the papers and making phenoData.txt...Or, I did "log2(matrix(assayData))", then made an eset with this input file. > > Anyhow, I will go back and start from the RMA normalized values and replicates. > However, for 3 reps each for 3 genotypes: Hi, Franklin. Take a look at section 8.3 of the limma user guide. Your experiment fits that exactly. > After making an eset, > This contrast matrix: > contrastMatrix=c(0,0,1, 0,1,0, 1,0,0, 0,0,2, 0,2,0, 2,0,0, 0,0,3, 0,3,0, 3,0,0) > should work, right? > Or, is another format, i.e. -1,.. ; {1,1,1}, a better option for comparision? > If its 1,1,1, for one genotype, contrast with the other 2 genotypes<- still cannot get $df.residuals correct? > Ambrosia Gala Melrose >> 1 1 0 0 >> 2 1 -1 0 >> 3 1 0 -1 > ---didn't work either--- > > Is there a way to coerce limma to accept a variable with only 2 levels? Yes. Limma accepts factors with only 2 levels--no coercion necessary. See section 8.2 of the limma user guide for an example. > I can write an ANOVA that accepts a factor with just 1 level...it's kinda of odd I can't do this with limma. > For example, sex is M an F...only 2 levels. If I'm not mistaken, limma require 'more than 2 levels', right? No, that is not correct. Limma will accept a factor with only 2 levels. You will definitely benefit from reading the limma user guide. Try following the examples in section 8.2 and 8.3 to get a better sense of how limma works. Hope that helps. Sean > But, limma is very useful, and efficient. > > Hope this helps...I'm here all night! > Regards, > Franklin > > > ________________________________________ > From: seandavi at gmail.com [seandavi at gmail.com] on behalf of Sean Davis [sdavis2 at mail.nih.gov] > Sent: Tuesday, May 07, 2013 3:12 PM > To: FRANKLIN JOHNSON [guest] > Cc: bioconductor at r-project.org; franklin.johnson at wsu.edu > Subject: Re: [BioC] No $df.residual > > Hi, Franklin. See below. > > On Tue, May 7, 2013 at 6:04 PM, FRANKLIN JOHNSON [guest] > <guest at="" bioconductor.org=""> wrote: >> >> Hello, >> >> I want to determine differences between three genotypes. >> I'm using an exprs(eset). >> I made: >> contrastMatrix >> Ambrosia Gala Melrose >> 1 1 0 0 >> 2 0 1 0 >> 3 0 0 1 >> However, in fit2() >> $df.residual >> [1] 0 0 0 0 0 >> 68660 more elements ... >> >> $sigma >> [1] NA NA NA NA NA >> 68660 more elements ... >> I looked back to fit() and had the same output. >> However, my design matrix should allow me to compute differences. Does it say somewhere reps are necessary, other times seems to suggest need based on hypothesis. >> > > Yes, you need replicates to have residual degrees of freedom and to > perform a statistical test. > >> I already computed the average. > > Might be obvious, but the average of what? > >> I can also compute the stats for this as well, if needed. >> Can I create an object of this to use with limma? > > Again, can your clarify what data you mean to use with limma? > > Sean > >> On the other hand, >> $qr >> Ambrosia Gala Melrose >> 1 -1 0 0 >> 2 0 -1 0 >> 3 0 0 1 >> >> Also, this contrastMatrix doesn't fit. >> >> Regards, >> Franklin >> >> >> >> >> >> >> -- output of sessionInfo(): >> >> R 2.15.1 >>> objects() >> [1] "constrast.matrix" "contrastNames" "contrastsMatrix" >> [4] "design" "eFBestN" "eFBestNlog2t" >> [7] "eSetlog2_eFBestN" "exprs" "fit" >> [10] "fit2" "geneID" "HistogramPlot" >> [13] "limmaGUIenvironment" "log2_eFBestN" "mydesign" >> [16] "myfit" "NEOffsetDefault" "numParameters" >> [19] "parameterNames" "pDataN" "pDatarootstocKlog2" >> [22] "pDatarootstocNlog2" "pDatascioNlog2" "phenoDatN" >> [25] "SampleNames" "scion.phenoData" "ss.rootstock.eFBestNlog2t" >> [28] "ss.rootstock.log2" "ss.rootstock.log2t" "ss.scion.eFBestNlog2t" >> [31] "ss.scion.log2" "ss.scion.log2t" "targets" >> ##################### >> function (package = NULL) >> { >> z <- list() >> z$R.version <- R.Version() >> z$platform <- z$R.version$platform >> if (nzchar(.Platform$r_arch)) >> z$platform <- paste(z$platform, .Platform$r_arch, sep = "/") >> z$platform <- paste(z$platform, " (", 8 >> >> >> -- >> Sent via the guest posting facility at bioconductor.org. >> >> _______________________________________________ >> 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 > > > _______________________________________________ > 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