Dear BioC, Please guide me in experient..Howmany Cells I need to collect in order to be confident in my LIMMA statistical analysis? I think LIMMA is the good approach because I hvae more than 2 conditions. Please see below information. I would like to perform experient of 5 genes with 4 different groups of cells. ( Small scale array) GeneA GeneB GeneC GeneD GeneE Group1 Group2 Group3 Group4 How can I define Design Matrix for these 4 different groups of cells? Can I do: Group1-Group2, Group1-Group3, Group1-Group4 Group2-Group3, Group2-Group4 Group3-Group4 I would like to study on SMALL scale Array...Is there any approach which I could seek? Please, let me know if anybody has performed such design or analysis? Thank you so much in advance, Saurin

You could use limma for this experiment but since you cannot use the eBayes procedure with so few genes you might be better off using a simpler statistical package such as SAS or MINITAB. The routine you want is called one-way ANOVA. Surely you do not intend to use microarrays with so few genes. This cannot be cost-effective? You need to have biological replication within group to do the analysis you suggest. --Naomi At 01:31 PM 6/23/2005, Saurin Jani wrote: >Dear BioC, > >Please guide me in experient..Howmany Cells I need to >collect in order to be confident in my LIMMA >statistical analysis? I think LIMMA is the good >approach because I hvae more than 2 conditions. Please >see below information. > >I would like to perform experient of 5 genes with 4 >different groups of cells. ( Small scale array) > > > GeneA GeneB GeneC GeneD GeneE >Group1 >Group2 >Group3 >Group4 > >How can I define Design Matrix for these 4 different >groups of cells? > >Can I do: > >Group1-Group2, Group1-Group3, Group1-Group4 > >Group2-Group3, Group2-Group4 > >Group3-Group4 > > >I would like to study on SMALL scale Array...Is there >any approach which I could seek? > >Please, let me know if anybody has performed such >design or analysis? > >Thank you so much in advance, >Saurin > >_______________________________________________ >Bioconductor mailing list >Bioconductor at stat.math.ethz.ch >https://stat.ethz.ch/mailman/listinfo/bioconductor Naomi S. Altman 814-865-3791 (voice) Associate Professor Bioinformatics Consulting Center Dept. of Statistics 814-863-7114 (fax) Penn State University 814-865-1348 (Statistics) University Park, PA 16802-2111