Hi, You may check if you have missing values 'NA's in your data. Best wishes Julian On 27/02/14 21:53, J Brown [guest] wrote: > > 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 > > -- > Sent via the guest posting facility at bioconductor.org. > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >

[cc:ing the maintainer of pcaMethods] Author of matrixStats::weightedMedian() here. I won't solve OPs problem but I'll add some clues to the non-informative error message from weightedMedian(). On Mon, Mar 3, 2014 at 9:35 AM, Julian Gehring <julian.gehring at="" embl.de=""> wrote: > Hi, > > You may check if you have missing values 'NA's in your data. > > Best wishes > Julian > > > On 27/02/14 21:53, J Brown [guest] wrote: >> >> 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) That error in weightedMedian() occurs because there are missing values in either in x[keep]/a or in the weights abs(a) and argument 'na.rm' defaults to NA(*). It's better if robustSvd() would call weightedMedian(x[keep]/a, abs(a), na.rm=TRUE, interpolate=FALSE), or possibly na.rm=FALSE. (*) With weightedMedian(..., na.rm=NA) one tells that function to trust the data (including the weights) to have no missing values. This option exists for efficiency reasons. If there are missing values, the na.rm=TRUE should be used. If there could be missing value, na.rm=FALSE should be used (in case NA is returned if there are missing values). That the default is NA is unconventional and I may consider changing matrixStats to use the more commonly used na.rm=FALSE (no promises though). /Henrik >> >> -- 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 >> >> -- >> Sent via the guest posting facility at bioconductor.org. >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at r-project.org >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >> > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor

Hi Henning, I'm not the OP, you would have to ask him for the data. Best wishes Julian On 12/03/14 22:25, Henning Redestig wrote: > Sorry for the slow reply, I changed the call to weightedMedian to use > na.rm=TRUE but not sure if it solves the issue.. Julian, any chance you > could share the data? (preferably subsetted to the minimum size that > still causes the error) > > cheers, Henning (pcaMethods maintainer) > > > 2014-03-03 20:34 GMT+01:00 Henrik Bengtsson <hb at="" biostat.ucsf.edu=""> <mailto:hb at="" biostat.ucsf.edu="">>: > > [cc:ing the maintainer of pcaMethods] > > Author of matrixStats::weightedMedian() here. I won't solve OPs > problem but I'll add some clues to the non-informative error message > from weightedMedian(). > > On Mon, Mar 3, 2014 at 9:35 AM, Julian Gehring > <julian.gehring at="" embl.de="" <mailto:julian.gehring="" at="" embl.de="">> wrote: > > Hi, > > > > You may check if you have missing values 'NA's in your data. > > > > Best wishes > > Julian > > > > > > On 27/02/14 21:53, J Brown [guest] wrote: > >> > >> 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) > > That error in weightedMedian() occurs because there are missing values > in either in x[keep]/a or in the weights abs(a) and argument 'na.rm' > defaults to NA(*). It's better if robustSvd() would call > weightedMedian(x[keep]/a, abs(a), na.rm=TRUE, interpolate=FALSE), or > possibly na.rm=FALSE. > > (*) With weightedMedian(..., na.rm=NA) one tells that function to > trust the data (including the weights) to have no missing values. > This option exists for efficiency reasons. If there are missing > values, the na.rm=TRUE should be used. If there could be missing > value, na.rm=FALSE should be used (in case NA is returned if there are > missing values). That the default is NA is unconventional and I may > consider changing matrixStats to use the more commonly used > na.rm=FALSE (no promises though). > > /Henrik > > >> > >> -- 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 > >> > >> -- > >> Sent via the guest posting facility at bioconductor.org > <http: bioconductor.org="">. > >> > >> _______________________________________________ > >> Bioconductor mailing list > >> Bioconductor at r-project.org <mailto:bioconductor at="" r-project.org=""> > >> https://stat.ethz.ch/mailman/listinfo/bioconductor > >> Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > >> > > > > _______________________________________________ > > Bioconductor mailing list > > Bioconductor at r-project.org <mailto:bioconductor at="" r-project.org=""> > > https://stat.ethz.ch/mailman/listinfo/bioconductor > > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > >