Dear Maintainer, I'm analyzing metabolomic LC-MS intensity values. To reduced these large numbers, I log transformed the dataset. To replace any Inf/-Inf/NA with a zero: > logtransfo[!is.finite(logtransfo)]<-0 and checked for NAs: > is.na(logtransfo)) CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 123.1166295 FALSE FALSE FALSE FALSE 109.1012434 FALSE FALSE FALSE FALSE All cells printed FALSE. I made contrasts using limma package. > head(wCA12m) CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 123.1166295 " 0.018961357" "-0.091637119" " 3.268257162" "-1.025643391" 109.1012434 " 0.146168274" "-0.055655014" " 3.172041095" "-0.969301615" Made an expression set: > wCA12me ExpressionSet (storageMode: lockedEnvironment) assayData: 124 features, 4 samples element names: exprs protocolData: none phenoData: none featureData: none experimentData: use 'experimentData(object)' Annotation: is.na(exprs(wCA12me)) CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 123.1166295 FALSE FALSE FALSE FALSE 109.1012434 FALSE FALSE FALSE FALSE I loaded library(Mfuzz), and went through the steps as indicated in the manual. > wCA12me.r=filter.NA(wCA12me) 0 genes excluded. > wCA12me.f=fill.NA(wCA12me.r, mode="knn") #after failing to standardise, I also tried using the other mode options. I could get a nice plot with "knn" and "knnw", but using "mean" and "median" gave an error for fill.NA. > tmp=filter.std(wCA12me, min.std=0) 0 genes excluded. Also, changed the min.std value. > tmp=filter.std(wCA12me, min.std=2) 67 genes excluded. For either case of changing the mode="", and min.std="", I always get the same error message when using the call to 'standardise': > wCA12me.s=standardise(wCA12me.f) Error in data[i, ] - mean(data[i, ], na.rm = TRUE) : non-numeric argument to binary operator In addition: Warning message: In mean.default(data[i, ], na.rm = TRUE) : argument is not numeric or logical: returning NA Checking my file several times, I showed that no data points contain NA. I think I understand what the error is saying, but I didn't expect negative values to affect the clustering algorithm. I was able to complete the package with non- transformed values, however, the transformed values give slightly different results, and wanted to compare the non-transformed and log- transformed datasets. This being LC-MS metabolomic data, could I use a different function to transform the data to not get negative values? Thanks for your attention. Regards, Franklin -- output of sessionInfo(): R version 3.0.1 (2013-05-16) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 [2] LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] tcltk parallel stats graphics grDevices utils datasets [8] methods base other attached packages: [1] limma_3.16.5 Mfuzz_2.18.0 DynDoc_1.38.0 [4] widgetTools_1.38.0 e1071_1.6-1 class_7.3-7 [7] Biobase_2.20.0 BiocGenerics_0.6.0 BiocInstaller_1.10.2 loaded via a namespace (and not attached): [1] tkWidgets_1.38.0 tools_3.0.1 -- Sent via the guest posting facility at bioconductor.org.

Dear Franklin, it looks like that your numbers are in fact characters > head(wCA12m) CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 123.1166295 " 0.018961357" "-0.091637119" " 3.268257162" "-1.025643391" 109.1012434 " 0.146168274" "-0.055655014" " 3.172041095" "-0.969301615" since quotation marks are appearing. Once you convert them in real numbers, it should be ok. hth, Matthias. Em 26-06-2013 22:17, FRANKLIN JOHNSON [guest] escreveu: > Dear Maintainer, > > I'm analyzing metabolomic LC-MS intensity values. > To reduced these large numbers, I log transformed the dataset. To replace any Inf/-Inf/NA with a zero: >> logtransfo[!is.finite(logtransfo)]<-0 > and checked for NAs: >> is.na(logtransfo)) > CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 > 123.1166295 FALSE FALSE FALSE FALSE > 109.1012434 FALSE FALSE FALSE FALSE > > All cells printed FALSE. > I made contrasts using limma package. >> head(wCA12m) > CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 > 123.1166295 " 0.018961357" "-0.091637119" " 3.268257162" "-1.025643391" > 109.1012434 " 0.146168274" "-0.055655014" " 3.172041095" "-0.969301615" > > Made an expression set: >> wCA12me > ExpressionSet (storageMode: lockedEnvironment) > assayData: 124 features, 4 samples > element names: exprs > protocolData: none > phenoData: none > featureData: none > experimentData: use 'experimentData(object)' > Annotation: > > is.na(exprs(wCA12me)) > CA.2wk11.H11 CA.4wk11.CA.2wk11 CA.8wk11.CA.4wk11 CA.12wk11.CA.8wk11 > 123.1166295 FALSE FALSE FALSE FALSE > 109.1012434 FALSE FALSE FALSE FALSE > > I loaded library(Mfuzz), and went through the steps as indicated in the manual. > >> wCA12me.r=filter.NA(wCA12me) > 0 genes excluded. >> wCA12me.f=fill.NA(wCA12me.r, mode="knn") #after failing to standardise, I also tried using the other mode options. > I could get a nice plot with "knn" and "knnw", but using "mean" and "median" gave an error for fill.NA. > >> tmp=filter.std(wCA12me, min.std=0) > 0 genes excluded. > > Also, changed the min.std value. >> tmp=filter.std(wCA12me, min.std=2) > 67 genes excluded. > > For either case of changing the mode="", and min.std="", > I always get the same error message when using the call to 'standardise': > >> wCA12me.s=standardise(wCA12me.f) > Error in data[i, ] - mean(data[i, ], na.rm = TRUE) : > non-numeric argument to binary operator > In addition: Warning message: > In mean.default(data[i, ], na.rm = TRUE) : > argument is not numeric or logical: returning NA > > Checking my file several times, I showed that no data points contain NA. I think I understand what the error is saying, but I didn't expect negative values to affect > the clustering algorithm. I was able to complete the package with non-transformed values, however, the transformed values give slightly different results, and wanted to compare the non-transformed and log- transformed datasets. > > This being LC-MS metabolomic data, could I use a different function to transform the data to not get negative values? > > Thanks for your attention. > Regards, > Franklin > > > > > -- output of sessionInfo(): > > R version 3.0.1 (2013-05-16) > Platform: x86_64-w64-mingw32/x64 (64-bit) > > locale: > [1] LC_COLLATE=English_United States.1252 > [2] LC_CTYPE=English_United States.1252 > [3] LC_MONETARY=English_United States.1252 > [4] LC_NUMERIC=C > [5] LC_TIME=English_United States.1252 > > attached base packages: > [1] tcltk parallel stats graphics grDevices utils datasets > [8] methods base > > other attached packages: > [1] limma_3.16.5 Mfuzz_2.18.0 DynDoc_1.38.0 > [4] widgetTools_1.38.0 e1071_1.6-1 class_7.3-7 > [7] Biobase_2.20.0 BiocGenerics_0.6.0 BiocInstaller_1.10.2 > > loaded via a namespace (and not attached): > [1] tkWidgets_1.38.0 tools_3.0.1 > > -- > Sent via the guest posting facility at bioconductor.org. > > -- ************************************************************ Dr. Matthias E. Futschik Principal Investigator in Systems Biology and Bioinformatics Centre for Molecular and Structural Biomedicine University of Algarve, Campus of Gambelas 8005-139 Faro, Portugal url: www.sysbiolab.eu email: mfutschik at ualg.pt