Hi Gordon and everyone I'm having difficulty running the background correction function in LIMMA I'm trying to use the "minimum" option but get the following error message: > AR123rep6RGback <- backgroundCorrect(AR123rep6RG, method="minimum") Error in if (any(i)) { : missing value where TRUE/FALSE needed options "none" & "half", appear to work perfectly fine, any ideas ? once I have "corrected" I take it this just creates another RG object ? which can then be used in normalizeWithinArrays/normalizeBetweenArrays ? ALSO Has anyone used the QVALUE function from John Storey with limma ? are then any functions in limma that support the use of QVALUE if not do you have any suggestions as to the best way to use it with limma. If it is somehow possible to add another column of data to the toptable command to display M, t, P.values, B and q.values ??? thanks for any advice Jason -- -------------------------------- Jason Skelton Pathogen Microarrays Wellcome Trust Sanger Institute Hinxton Cambridge CB10 1SA Tel +44(0)1223 834244 Ext 7123 Fax +44(0)1223 494919

At 01:54 AM 2/10/2003, Jason Skelton wrote: >Hi Gordon and everyone > >I'm having difficulty running the background correction function in LIMMA >I'm trying to use the "minimum" option but get the following error message: > > > AR123rep6RGback <- backgroundCorrect(AR123rep6RG, method="minimum") >Error in if (any(i)) { : missing value where TRUE/FALSE needed > >options "none" & "half", appear to work perfectly fine, any ideas ? My guess is that there are missing values in your foreground or background intensities. Assuming that is the problem, I have implemented a fix in limma 1.2.7. >once I have "corrected" I take it this just creates another RG object ? >which can then be used in normalizeWithinArrays/normalizeBetweenArrays ? Yes. >ALSO > >Has anyone used the QVALUE function from John Storey with limma ? >are then any functions in limma that support the use of QVALUE >if not do you have any suggestions as to the best way to use it with limma. No. John Storey's qvalue() function is copyrighted by him and so cannot be distributed with Bioconductor. In any case, it wouldn't change the limma results. The limma functions are designed to give a best ranking of the genes in order of evidence for differential expression. Although p-values are output, they are intended for ranking genes and should not be trusted as absolute measures of significance because they rely on assumptions of independence and normality which are surely not true (as do all similar methods). The qvalue() function won't change the results because it doesn't change the ranking of the genes. It's simply a more sophisticated version of the adjust="fdr" option already provided in toptable. >If it is somehow possible to add another column of data to the toptable >command to display M, t, P.values, B and q.values ??? You can always add another column yourself to the output from toptable since toptable simply produces a data frame. BTW, my personal approach is to estimate actual false discovery rates from spike-in control data rather than to try to estimate them from p-values in the absence of knowledge of the independence between genes. Gordon >thanks for any advice > >Jason > >-- >-------------------------------- >Jason Skelton >Pathogen Microarrays >Wellcome Trust Sanger Institute >Hinxton >Cambridge >CB10 1SA > >Tel +44(0)1223 834244 Ext 7123 >Fax +44(0)1223 494919