Dear bioconducter mailing list I am a PhD student in plant breeding department in Norway. I am using your limma package for analyzing my RNA-seq data. Since I am not a statistician, so I am asking you a very small question from you. I have a 2 factorial experiment with a split plot design, where block was the main plot and lane was in sub plot. Now I want to fit the block as fixed effect and lane as a random effect. Could you please kindly tell me very briefly that how can I define fixed and random effect together in limma package? I read section 9.7 and 11.3 where it was described for microarray data but dont know how to handel with voom function for RNAseq data. Best wishes Fabina Oslo, Norway [[alternative HTML version deleted]]

Dear Fabina, The same instructions apply exactly the same for RNA-seq as for microarrays. (This is one of the advantages of voom.) Best wishes Gordon > Date: Thu, 7 Nov 2013 16:47:23 +0100 > From: sci yasmin <sci.yasmin at="" gmail.com=""> > To: bioconductor at r-project.org > Subject: [BioC] Random effect for RNAseq data in Limma package > > Dear bioconducter mailing list > > I am a PhD student in plant breeding department in Norway. I am using > your limma package for analyzing my RNA-seq data. Since I am not a > statistician, so I am asking you a very small question from you. I have > a 2 factorial experiment with a split plot design, where block was the > main plot and lane was in sub plot. Now I want to fit the block as fixed > effect and lane as a random effect. Could you please kindly tell me very > briefly that how can I define fixed and random effect together in limma > package? I read section 9.7 and 11.3 where it was described for > microarray data but dont know how to handel with voom function for > RNAseq data. > > Best wishes > > Fabina > Oslo, Norway ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}