[BioC] two questions about limma

[zhaodj at ioz.ac.cn]

Dear members,
I encounter two problems when analysing the microarray data employing the
package limma. I am using R ver.2.4.1 and limma ver.2.9.13.


-------Question 1-------------
After the backgroundCorrect step, the software gives a series of warning
messages as follows:
> RG.b<-backgroundCorrect(RG,method="normexp",offset=0)
Corrected array 1
Corrected array 2
Corrected array 3
Corrected array 4
Corrected array 5
Corrected array 6
Corrected array 7
Corrected array 8
Corrected array 9
Corrected array 10
Corrected array 11
Corrected array 12
Corrected array 13
Corrected array 14
Corrected array 15
Corrected array 16
Corrected array 17
Corrected array 18
Warning messages:
1: Produced NaNs in: log(x)
2: Produced NaNs in: log(x)
3: Produced NaNs in: log(x)

The datails of the medthod "normexp" is
normexp = {
        for (j in 1:ncol(RG$R)) {
            x <- RG$G[, j] - RG$Gb[, j]
            out <- normexp.fit(x)
            RG$G[, j] <- normexp.signal(out$par, x)
            x <- RG$R[, j] - RG$Rb[, j]
            out <- normexp.fit(x)
            RG$R[, j] <- normexp.signal(out$par, x)
            if (verbose)
                cat("Corrected array", j, "\n")
        }

I find that some NaNs occur when running the code "out <- normexp.fit(x)".
I don't know how to deal with the NaNs.If the NaNs do not influence the
selection of the differentially expressed genes, I will ignore them. If
not, I seek for your suggestion.


-------Question 2-------------
Another problem is from the duplicateCorrelation. The function glmgam.fit
is from the package statmod.
>corMA.p<-duplicateCorrelation(MA.p,design,ndups=2)
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)

I don't know the meaning of this warning. Can I ignore them and proceed to
the subsequent analysis of the differentially expressed genes? Will the
two shortcomings mentioned in the warnings affect the reliability of the
differentially expressed genes? If it does,please give some advice.


Thanks to all of you!