Dear edgeR maintainers, I have some troubles setting up the correct design for my DE experiment. I now how my experiment design should look like and that is like this: > design subject1 subject2 subject3 subject4 S7309 1 0 0 0 S7310 1 0 0 0 S7311 0 1 0 0 S7312 0 1 0 0 S7313 0 0 1 0 S7314 0 0 1 0 S7315 0 0 0 1 S7316 0 0 0 1 attr(,"assign") [1] 1 1 1 1 attr(,"contrasts") attr(,"contrasts")$subject [1] "contr.treatment" After that i make my contrasts: > makeContrasts(subject1,subject2,subject3,subject4, levels = design) Contrasts Levels subject1 subject2 subject3 subject4 subject1 1 0 0 0 subject2 0 1 0 0 subject3 0 0 1 0 subject4 0 0 0 1 This all looks right since i need to compare the subjects with each other. But when i run my analysis function which looks like this: library( edgeR ); library( ggplot2 ); library( reshape ); library( FactoMineR ); analyse <- function( counts, design, contrast, name, style ) { counts <- counts[ rowSums( counts, na.rm = TRUE ) > 0, ]; y <- DGEList( counts = counts, genes = rownames( counts ) ); y <- calcNormFactors( y ); y <- estimateGLMCommonDisp( y, design ); y <- estimateGLMTrendedDisp( y, design, df = 5 ); y <- estimateGLMTagwiseDisp( y, design ); fit <- glmFit( y, design ); lrt <- glmLRT( fit, contrast = contrast ); de <- decideTestsDGE( lrt, p = 0.05, adjust = "BH" ); cpmY <- cpm( y ); daf <- designAsFactor( design ); orderedDesign <- design[ order( daf, names( daf ) ), ]; tab <- data.frame( row.names = rownames( cpmY ), genes = rownames( cpmY ), de = de, cpmY[ ,order( daf, names( daf ) ) ] ); aRepTab <- topTags( lrt, n = nrow( counts ) )$table; aRepTab$rank <- 1:nrow( counts ); # repTab <- tab[ match( aRepTab$genes, rownames( tab ) ), ]; repTab <- merge( aRepTab, tab, by = "genes", sort = FALSE ); repTab <- repTab[ order( repTab$rank ), ]; # data.frame( # row.names = rownames( aRepTab ), # aRepTab, # tab[ match( aRepTab$genes, tab$genes ), ] # ) list( name = name, y = y, fit = fit, lrt = lrt, de = de, tab = tab, style = style, repTab = repTab, orderedDesign = orderedDesign ); } I got the following error: Error in mglmLevenberg(y, design = design, dispersion = dispersion, offset = offset, : BLAS/LAPACK routine 'DGEMM ' gave error code -13 5 mglmLevenberg(y, design = design, dispersion = dispersion, offset = offset, weights = weights, coef.start = start, maxit = 250) 4 glmFit.default(glmfit$counts, design = design0, offset = glmfit$offset, weights = glmfit$weights, dispersion = glmfit$dispersion, prior.count = 0) 3 glmFit(glmfit$counts, design = design0, offset = glmfit$offset, weights = glmfit$weights, dispersion = glmfit$dispersion, prior.count = 0) 2 glmLRT(fit, contrast = contrast) at diffexpr.R#15 1 analyse(counts, design, contrast, countsId, style) I tried to use different models but i cannot succeed to avoid the error for this comparison. (other comparisons do succeed) Any hints will be very appreciated. Thanks in advance! Best regards, Sander -- output of sessionInfo(): > sessionInfo() R version 3.1.0 (2014-04-10) Platform: x86_64-pc-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] splines stats graphics grDevices utils datasets methods base other attached packages: [1] FactoMineR_1.26 reshape_0.8.5 ggplot2_1.0.0 reshape2_1.4 edgeR_3.6.7 limma_3.20.8 loaded via a namespace (and not attached): [1] car_2.0-20 cluster_1.15.2 colorspace_1.2-4 digest_0.6.4 grid_3.1.0 gtable_0.1.2 [7] htmltools_0.2.4 lattice_0.20-29 leaps_2.9 MASS_7.3-33 munsell_0.4.2 nnet_7.3-8 [13] plyr_1.8.1 proto_0.3-10 Rcpp_0.11.2 rmarkdown_0.2.49 scales_0.2.4 scatterplot3d_0.3-35 [19] stringr_0.6.2 tools_3.1.0 yaml_2.1.13 -- Sent via the guest posting facility at bioconductor.org.

Hi Sander, On Aug 21, 2014 8:59 AM, "Sander [guest]" <guest at="" bioconductor.org=""> wrote: > > Dear edgeR maintainers, > > I have some troubles setting up the correct design for my DE experiment. I now how my experiment design should look like and that is like this: > > design > subject1 subject2 subject3 subject4 > S7309 1 0 0 0 > S7310 1 0 0 0 > S7311 0 1 0 0 > S7312 0 1 0 0 > S7313 0 0 1 0 > S7314 0 0 1 0 > S7315 0 0 0 1 > S7316 0 0 0 1 > attr(,"assign") > [1] 1 1 1 1 > attr(,"contrasts") > attr(,"contrasts")$subject > [1] "contr.treatment" > > After that i make my contrasts: > > makeContrasts(subject1,subject2,subject3,subject4, levels = design) This is where you have made a mistake. Toy should be subtracting one subject from another, depending on the contrasts you care about. The resulting contrasts matrix should have both positive and negative values, not just zeros and ones. See the edgeR users guide or limma users guide for examples. Best, Jim > Contrasts > Levels subject1 subject2 subject3 subject4 > subject1 1 0 0 0 > subject2 0 1 0 0 > subject3 0 0 1 0 > subject4 0 0 0 1 > > This all looks right since i need to compare the subjects with each other. But when i run my analysis function which looks like this: > > library( edgeR ); > library( ggplot2 ); > library( reshape ); > library( FactoMineR ); > > analyse <- function( counts, design, contrast, name, style ) { > counts <- counts[ rowSums( counts, na.rm = TRUE ) > 0, ]; > y <- DGEList( counts = counts, genes = rownames( counts ) ); > y <- calcNormFactors( y ); > y <- estimateGLMCommonDisp( y, design ); > y <- estimateGLMTrendedDisp( y, design, df = 5 ); > y <- estimateGLMTagwiseDisp( y, design ); > > fit <- glmFit( y, design ); > lrt <- glmLRT( fit, contrast = contrast ); > de <- decideTestsDGE( lrt, p = 0.05, adjust = "BH" ); > cpmY <- cpm( y ); > > daf <- designAsFactor( design ); > orderedDesign <- design[ order( daf, names( daf ) ), ]; > tab <- data.frame( > row.names = rownames( cpmY ), > genes = rownames( cpmY ), > de = de, > cpmY[ ,order( daf, names( daf ) ) ] > ); > > aRepTab <- topTags( lrt, n = nrow( counts ) )$table; > aRepTab$rank <- 1:nrow( counts ); > # repTab <- tab[ match( aRepTab$genes, rownames( tab ) ), ]; > > repTab <- merge( aRepTab, tab, by = "genes", sort = FALSE ); > repTab <- repTab[ order( repTab$rank ), ]; > # data.frame( > # row.names = rownames( aRepTab ), > # aRepTab, > # tab[ match( aRepTab$genes, tab$genes ), ] > # ) > > list( > name = name, > y = y, > fit = fit, > lrt = lrt, > de = de, > tab = tab, > style = style, > repTab = repTab, > orderedDesign = orderedDesign > ); > } > > I got the following error: > > Error in mglmLevenberg(y, design = design, dispersion = dispersion, offset = offset, : > BLAS/LAPACK routine 'DGEMM ' gave error code -13 > 5 mglmLevenberg(y, design = design, dispersion = dispersion, offset = offset, > weights = weights, coef.start = start, maxit = 250) > 4 glmFit.default(glmfit$counts, design = design0, offset = glmfit$offset, > weights = glmfit$weights, dispersion = glmfit$dispersion, > prior.count = 0) > 3 glmFit(glmfit$counts, design = design0, offset = glmfit$offset, > weights = glmfit$weights, dispersion = glmfit$dispersion, > prior.count = 0) > 2 glmLRT(fit, contrast = contrast) at diffexpr.R#15 > 1 analyse(counts, design, contrast, countsId, style) > > I tried to use different models but i cannot succeed to avoid the error for this comparison. (other comparisons do succeed) Any hints will be very appreciated. > > Thanks in advance! > > Best regards, > > Sander > > -- output of sessionInfo(): > > > sessionInfo() > R version 3.1.0 (2014-04-10) > Platform: x86_64-pc-linux-gnu (64-bit) > > locale: > [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 > [6] LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C > [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C > > attached base packages: > [1] splines stats graphics grDevices utils datasets methods base > > other attached packages: > [1] FactoMineR_1.26 reshape_0.8.5 ggplot2_1.0.0 reshape2_1.4 edgeR_3.6.7 limma_3.20.8 > > loaded via a namespace (and not attached): > [1] car_2.0-20 cluster_1.15.2 colorspace_1.2-4 digest_0.6.4 grid_3.1.0 gtable_0.1.2 > [7] htmltools_0.2.4 lattice_0.20-29 leaps_2.9 MASS_7.3-33 munsell_0.4.2 nnet_7.3-8 > [13] plyr_1.8.1 proto_0.3-10 Rcpp_0.11.2 rmarkdown_0.2.49 scales_0.2.4 scatterplot3d_0.3-35 > [19] stringr_0.6.2 tools_3.1.0 yaml_2.1.13 > > -- > 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 [[alternative HTML version deleted]]