[BioC] warning messages from duplicateCorrelation in limma

Na, Ren Na at uthscsa.edu
Thu Nov 4 00:14:18 CET 2004


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

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