Dear BioC, I'm attempting to use the duplicateCorrelation function within limma to control for fact that tissues being studied come from the same animals. I understand that for this work appropriately, dupfit$consensus needs to be positive, which at "1", it is. But such an exact value is concerning to my inexperienced eye. I'd greatly appreciate hearing from people with experience using duplicateCorrelation what this outcome represents and if indeed is something to be wary of and perhaps omitted. With thanks in advance, cheers, Karl > design <- model.matrix(~Time * Pperiod * Tissue - Time : Pperiod : Tissue) > source(.trPaths[5], echo=TRUE, max.deparse.length=150) > dupfit <- duplicateCorrelation(rma.pp, design, ndups=1, block=Animal) > dupfit$consensus #remembering to check that dupfit$consensus is positive. [1] 1 There were 50 or more warnings (use warnings() to see the first 50) > warnings() Warning messages: 1: In sqrt(dfitted.values) : NaNs produced 2: In sqrt(dfitted.values) : NaNs produced 3: In sqrt(dfitted.values) : NaNs produced 4: In sqrt(dfitted.values) : NaNs produced 5: In sqrt(dfitted.values) : NaNs produced 6: In sqrt(dfitted.values) : NaNs produced 7: In sqrt(dfitted.values) : NaNs produced 8: In sqrt(dfitted.values) : NaNs produced 9: In sqrt(dfitted.values) : NaNs produced 10: In sqrt(dfitted.values) : NaNs produced 11: In sqrt(dfitted.values) : NaNs produced 12: In sqrt(dfitted.values) : NaNs produced 13: In sqrt(dfitted.values) : NaNs produced 14: In sqrt(dfitted.values) : NaNs produced 15: In sqrt(dfitted.values) : NaNs produced 16: In sqrt(dfitted.values) : NaNs produced 17: In sqrt(dfitted.values) : NaNs produced 18: In sqrt(dfitted.values) : NaNs produced 19: In sqrt(dfitted.values) : NaNs produced 20: In sqrt(dfitted.values) : NaNs produced 21: In sqrt(dfitted.values) : NaNs produced 22: In sqrt(dfitted.values) : NaNs produced 23: In sqrt(dfitted.values) : NaNs produced 24: In sqrt(dfitted.values) : NaNs produced 25: In sqrt(dfitted.values) : NaNs produced 26: In sqrt(dfitted.values) : NaNs produced 27: In sqrt(dfitted.values) : NaNs produced 28: In sqrt(dfitted.values) : NaNs produced 29: In sqrt(dfitted.values) : NaNs produced 30: In sqrt(dfitted.values) : NaNs produced 31: In sqrt(dfitted.values) : NaNs produced 32: In sqrt(dfitted.values) : NaNs produced 33: In sqrt(dfitted.values) : NaNs produced 34: In sqrt(dfitted.values) : NaNs produced 35: In sqrt(dfitted.values) : NaNs produced 36: In sqrt(dfitted.values) : NaNs produced 37: In sqrt(dfitted.values) : NaNs produced 38: In sqrt(dfitted.values) : NaNs produced 39: In sqrt(dfitted.values) : NaNs produced 40: In sqrt(dfitted.values) : NaNs produced 41: In sqrt(dfitted.values) : NaNs produced 42: In sqrt(dfitted.values) : NaNs produced 43: In sqrt(dfitted.values) : NaNs produced 44: In sqrt(dfitted.values) : NaNs produced 45: In sqrt(dfitted.values) : NaNs produced 46: In sqrt(dfitted.values) : NaNs produced 47: In sqrt(dfitted.values) : NaNs produced 48: In sqrt(dfitted.values) : NaNs produced 49: In sqrt(dfitted.values) : NaNs produced 50: In sqrt(dfitted.values) : NaNs produced > -- Karl Brand Department of Genetics Erasmus MC Dr Molewaterplein 50 3015 GE Rotterdam T +31 (0)10 704 3457 | F +31 (0)10 704 4743 | M +31 (0)642 777 268

I see now that i can not proceed with such a design including duplicateCorrelation (output below). Perhaps it results from trying to do to much with too few observations/replicates. I'd still really like to hear explanations why this might be so. cheers, Karl > fit <- lmFit(rma.pp, design, correlation=dupfit$consensus, block=Animal) Error in chol.default(V) : the leading minor of order 2 is not positive definite > On 5/24/2010 3:18 PM, Karl Brand wrote: > Dear BioC, > > I'm attempting to use the duplicateCorrelation function within limma to > control for fact that tissues being studied come from the same animals. > I understand that for this work appropriately, dupfit$consensus needs to > be positive, which at "1", it is. > > But such an exact value is concerning to my inexperienced eye. > > I'd greatly appreciate hearing from people with experience using > duplicateCorrelation what this outcome represents and if indeed is > something to be wary of and perhaps omitted. > > With thanks in advance, > > cheers, > > Karl > >> design <- model.matrix(~Time * Pperiod * Tissue - Time : Pperiod : > Tissue) >> source(.trPaths[5], echo=TRUE, max.deparse.length=150) > >> dupfit <- duplicateCorrelation(rma.pp, design, ndups=1, block=Animal) > >> dupfit$consensus #remembering to check that dupfit$consensus is > positive. > [1] 1 > There were 50 or more warnings (use warnings() to see the first 50) >> warnings() > Warning messages: > 1: In sqrt(dfitted.values) : NaNs produced > 2: In sqrt(dfitted.values) : NaNs produced > 3: In sqrt(dfitted.values) : NaNs produced > 4: In sqrt(dfitted.values) : NaNs produced > 5: In sqrt(dfitted.values) : NaNs produced > 6: In sqrt(dfitted.values) : NaNs produced > 7: In sqrt(dfitted.values) : NaNs produced > 8: In sqrt(dfitted.values) : NaNs produced > 9: In sqrt(dfitted.values) : NaNs produced > 10: In sqrt(dfitted.values) : NaNs produced > 11: In sqrt(dfitted.values) : NaNs produced > 12: In sqrt(dfitted.values) : NaNs produced > 13: In sqrt(dfitted.values) : NaNs produced > 14: In sqrt(dfitted.values) : NaNs produced > 15: In sqrt(dfitted.values) : NaNs produced > 16: In sqrt(dfitted.values) : NaNs produced > 17: In sqrt(dfitted.values) : NaNs produced > 18: In sqrt(dfitted.values) : NaNs produced > 19: In sqrt(dfitted.values) : NaNs produced > 20: In sqrt(dfitted.values) : NaNs produced > 21: In sqrt(dfitted.values) : NaNs produced > 22: In sqrt(dfitted.values) : NaNs produced > 23: In sqrt(dfitted.values) : NaNs produced > 24: In sqrt(dfitted.values) : NaNs produced > 25: In sqrt(dfitted.values) : NaNs produced > 26: In sqrt(dfitted.values) : NaNs produced > 27: In sqrt(dfitted.values) : NaNs produced > 28: In sqrt(dfitted.values) : NaNs produced > 29: In sqrt(dfitted.values) : NaNs produced > 30: In sqrt(dfitted.values) : NaNs produced > 31: In sqrt(dfitted.values) : NaNs produced > 32: In sqrt(dfitted.values) : NaNs produced > 33: In sqrt(dfitted.values) : NaNs produced > 34: In sqrt(dfitted.values) : NaNs produced > 35: In sqrt(dfitted.values) : NaNs produced > 36: In sqrt(dfitted.values) : NaNs produced > 37: In sqrt(dfitted.values) : NaNs produced > 38: In sqrt(dfitted.values) : NaNs produced > 39: In sqrt(dfitted.values) : NaNs produced > 40: In sqrt(dfitted.values) : NaNs produced > 41: In sqrt(dfitted.values) : NaNs produced > 42: In sqrt(dfitted.values) : NaNs produced > 43: In sqrt(dfitted.values) : NaNs produced > 44: In sqrt(dfitted.values) : NaNs produced > 45: In sqrt(dfitted.values) : NaNs produced > 46: In sqrt(dfitted.values) : NaNs produced > 47: In sqrt(dfitted.values) : NaNs produced > 48: In sqrt(dfitted.values) : NaNs produced > 49: In sqrt(dfitted.values) : NaNs produced > 50: In sqrt(dfitted.values) : NaNs produced >> > > > -- Karl Brand Department of Genetics Erasmus MC Dr Molewaterplein 50 3015 GE Rotterdam T +31 (0)10 704 3457 | F +31 (0)10 704 4743 | M +31 (0)642 777 268