Hi I have an another question about function duplicateCorrelation for my another data set which is four pairs of dye swap, four wild type biological replicates and four mutant biological replicates. When I run this function, I got Warning messages. I tried in two ways, 1) I only assigned weight 0 to missing spots which were not printed on our slides by doing w<-modifyWeights(RG$weights,status=RG$genes$Status, "miss",0) RG$weights<-w and when I run >design<-cbind(Dye=1, XpavsWt=c(1,-1,1,-1,1,-1,1,-1)) >pair<-c(1,1,2,2,3,3,4,4) > corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) Warning messages: 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) 2: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) 3: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) 4: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) corfit$consensus is -0.28 2) I assigned weight 0 to missing spots and blank spots on our slides like w<-modifyWeights(RG$weights,status=RG$genes$Status, c("blank","miss"),c(0,0)) RG$weights<-w and when I run > corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) Warning messages: 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, tol = tol, maxit = maxit, trace = trace) corfit$consensus is -0.31 Blank spots are the spot which were printed with buffer. In second way, corfit$consensus is increased a little bit and I got one warning in stead of four warnings. My questions are: what does the warning message mean? Does it mean the arrays' reproducibility is poor? Can I still get reasonable top list of genes by using the second way? I would appreciate any suggestion. Thanks in advance, Ren [[alternative HTML version deleted]]

> Date: Wed, 3 Nov 2004 17:14:18 -0600 > From: "Na, Ren" <na@uthscsa.edu> > Subject: [BioC] warning messages from duplicateCorrelation in limma > To: <bioconductor@stat.math.ethz.ch> > Message-ID: > <34263DF081CECE4F81FEF001C113CFA50206EA14@addax.win.uthscsa.edu> > Content-Type: text/plain > > Hi > I have an another question about function duplicateCorrelation for my another data set which is > four pairs of dye swap, four wild type biological replicates and four mutant biological > replicates. When I run this function, I got Warning messages. I tried in two ways, Firstly, warnings from duplicateCorrelation() are not a problem. The warnings affect only 4 genes out of many thousands. The consensus correlation will be little affected if at all because it is a robust average over all the genes. Secondly, assigning zero weight is not the way to remove missing or control spots. You should leave the weights as they are are and instead subject the data object. For example, isBlank <- (MA$genes$Status %in% c("blank","miss")) corfit <- duplicateCorrelation(MA[!isBlank,], design, ndups=1, block=pair) See the Weaver example in the Limma User's Guide for an example of the treatment of control spots. Gordon > 1) I only assigned weight 0 to missing spots which were not printed on our slides > by doing > w<-modifyWeights(RG$weights,status=RG$genes$Status, "miss",0) > RG$weights<-w > and when I run >>design<-cbind(Dye=1, XpavsWt=c(1,-1,1,-1,1,-1,1,-1)) >>pair<-c(1,1,2,2,3,3,4,4) >> corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) > Warning messages: > 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 2: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 3: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 4: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > > corfit$consensus is -0.28 > > 2) I assigned weight 0 to missing spots and blank spots on our slides like > w<-modifyWeights(RG$weights,status=RG$genes$Status, c("blank","miss"),c(0,0)) > RG$weights<-w > and when I run >> corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) > Warning messages: > 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > > corfit$consensus is -0.31 > > Blank spots are the spot which were printed with buffer. > In second way, corfit$consensus is increased a little bit and I got one warning in stead of four > warnings. > > My questions are: what does the warning message mean? Does it mean the arrays' reproducibility is > poor? Can I still get reasonable top list of genes by using the second way? I would appreciate any > suggestion. > > Thanks in advance, > Ren

Dr. Smyth, Thank you very much for your prompt reply. I tried remove missing and control spots exactly like the way you suggested before I sent my first email, and I got several same warnings too. But your explain clarified my thoughts and make me feel more comfortable with my data. Thanks again. Ren -----Original Message----- From: Gordon K Smyth [mailto:smyth@wehi.EDU.AU] Sent: Thu 11/4/2004 5:41 AM To: Na, Ren Cc: bioconductor@stat.math.ethz.ch Subject: [BioC] warning messages from duplicateCorrelation in limma > Date: Wed, 3 Nov 2004 17:14:18 -0600 > From: "Na, Ren" <na@uthscsa.edu> > Subject: [BioC] warning messages from duplicateCorrelation in limma > To: <bioconductor@stat.math.ethz.ch> > Message-ID: > <34263DF081CECE4F81FEF001C113CFA50206EA14@addax.win.uthscsa.edu> > Content-Type: text/plain > > Hi > I have an another question about function duplicateCorrelation for my another data set which is > four pairs of dye swap, four wild type biological replicates and four mutant biological > replicates. When I run this function, I got Warning messages. I tried in two ways, Firstly, warnings from duplicateCorrelation() are not a problem. The warnings affect only 4 genes out of many thousands. The consensus correlation will be little affected if at all because it is a robust average over all the genes. Secondly, assigning zero weight is not the way to remove missing or control spots. You should leave the weights as they are are and instead subject the data object. For example, isBlank <- (MA$genes$Status %in% c("blank","miss")) corfit <- duplicateCorrelation(MA[!isBlank,], design, ndups=1, block=pair) See the Weaver example in the Limma User's Guide for an example of the treatment of control spots. Gordon > 1) I only assigned weight 0 to missing spots which were not printed on our slides > by doing > w<-modifyWeights(RG$weights,status=RG$genes$Status, "miss",0) > RG$weights<-w > and when I run >>design<-cbind(Dye=1, XpavsWt=c(1,-1,1,-1,1,-1,1,-1)) >>pair<-c(1,1,2,2,3,3,4,4) >> corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) > Warning messages: > 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 2: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 3: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > 4: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > > corfit$consensus is -0.28 > > 2) I assigned weight 0 to missing spots and blank spots on our slides like > w<-modifyWeights(RG$weights,status=RG$genes$Status, c("blank","miss"),c(0,0)) > RG$weights<-w > and when I run >> corfit<-duplicateCorrelation(MA,design,ndups=1,block=pair) > Warning messages: > 1: Too much damping - convergence tolerance not achievable in: glmgam.fit(dx, dy, start = start, > tol = tol, maxit = maxit, trace = trace) > > corfit$consensus is -0.31 > > Blank spots are the spot which were printed with buffer. > In second way, corfit$consensus is increased a little bit and I got one warning in stead of four > warnings. > > My questions are: what does the warning message mean? Does it mean the arrays' reproducibility is > poor? Can I still get reasonable top list of genes by using the second way? I would appreciate any > suggestion. > > Thanks in advance, > Ren [[alternative HTML version deleted]]