[BioC] Problems with robustPca in pcaMethods

[J Brown [guest]]

Hi all;

I'm new to R and trying to use the pcaMethods package to analyze a qPCR dataset. My dataset contains many missing values and I think the module I want to use is robustPca, but when I try to apply it to my dataset I keep getting the error described below. Using nipalsPca on my dataset works without errors, so I don't think it's a data-format issue. Using robustPca on the pcaMethods sample dataset "metaboliteData", which has missing values, also works fine (although it warns about missing values), so it isn't a general problem with my install of R and the relevant packages. 

The traceback results seems to say that the error is caused by a weighted-median calculation that is part of the robustPca command, but I have no idea why this only comes up using my dataset: could it be because my dataset is already median-normalized (before importing to R)? Troubleshooting this is beyond my abilities at this point; I'd be grateful for any insight anyone can offer.

> pca_results <- pca(centered_data, method = "robustPca", nPcs = 10, center = FALSE)
Error in if (!all(tmp)) { : missing value where TRUE/FALSE needed
In addition: Warning message:
In robustPca(prepres$data, nPcs = nPcs, ...) :
  Data is incomplete, it is not recommended to use robustPca for missing value estimation

> traceback()
7: weightedMedian.default(x[keep]/a, abs(a), interpolate = FALSE)
6: weightedMedian(x[keep]/a, abs(a), interpolate = FALSE)
5: FUN(newX[, i], ...)
4: apply(x, 1, L1RegCoef, bk)
3: robustSvd(Matrix)
2: robustPca(prepres$data, nPcs = nPcs, ...)
1: pca(centered_data, method = "robustPca", nPcs = 10, center = FALSE)

 -- output of sessionInfo(): 

R version 3.0.2 (2013-09-25)
Platform: x86_64-apple-darwin10.8.0 (64-bit)

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] pcaMethods_1.52.1  Rcpp_0.11.0        matrixStats_0.8.14 Biobase_2.22.0     BiocGenerics_0.8.0

loaded via a namespace (and not attached):
[1] R.methodsS3_1.6.1 tools_3.0.2 

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