At 05:45 PM 31/03/2004, Binita Dutta wrote: >2) Please see the attached word file, where the MA plots flips when i >normalise between the arrays. I discussed this problem with few users of >bioconductor and they were not able to explain this problem. Before between-array normalization, you have lots of spots in the minimum possible intensities, i.e., 1, 2, 3, etc. After between-array normalization, you have lots of spots large but equal intensities, hence the pattern in your plot. I don't know why your data specifically has this pattern, but I suspect you have a lot of missing values. Between-array normalization cannot be recommended in general in the presence of lots of missing values. You need to force the intensities to be positive and non-missing. >3) As you can see below in the table P values are indeed 0.99999 etc for >top differentially expressed genes which is impossible!!! It is quite possible. Could it be that you are comparing multiple- testing adjusted p-values from limma with unadjusted p-values from another program? >4) As i understand from your explanation i have to >top<-topTable(fit,number=22680,adjust="fdr") > > and try to subset top and not the function topTable > >subset<-subset(top,P.Value<0.01,select=MA$genes)..............am i right? Sort of. Your 'select=' argument is still wrong. Please read the help for 'subset'. Gordon >Thanks in advance > >Binita