Hi,

I have been using DESeq2 for a while, it is a good tool, never had any issues. Now I am getting an error at rlog() using 'fast' which is essential AFAIAC:

> rldss<-rlog(ddss, fast=T)

Error in rlog(ddss, fast = T) : unused argument (fast = T)

I do note that the option is removed from the documentation. If this is the case can anyone specify why? And are there other quick ways to do this transform? It is purely to plot PCA.

Appreciate any help,

Bruce.

> sessionInfo()
R version 3.2.2 (2015-08-14)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 14.04.3 LTS

locale:
 [1] LC_CTYPE=en_IE.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_IE.UTF-8        LC_COLLATE=en_IE.UTF-8
 [5] LC_MONETARY=en_IE.UTF-8    LC_MESSAGES=en_IE.UTF-8
 [7] LC_PAPER=en_IE.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_IE.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets
[8] methods   base

other attached packages:
 [1] ggplot2_1.0.1              genefilter_1.52.0
 [3] DESeq2_1.10.0              RcppArmadillo_0.6.100.0.0
 [5] Rcpp_0.12.1                SummarizedExperiment_1.0.0
 [7] Biobase_2.30.0             GenomicRanges_1.22.0
 [9] GenomeInfoDb_1.6.0         IRanges_2.4.1
[11] S4Vectors_0.8.0            BiocGenerics_0.16.0
[13] BiocInstaller_1.20.0

loaded via a namespace (and not attached):
 [1] RColorBrewer_1.1-2   futile.logger_1.4.1  plyr_1.8.3
 [4] XVector_0.10.0       futile.options_1.0.0 tools_3.2.2
 [7] zlibbioc_1.16.0      rpart_4.1-10         digest_0.6.8
[10] RSQLite_1.0.0        annotate_1.48.0      gtable_0.1.2
[13] lattice_0.20-33      DBI_0.3.1            proto_0.3-10
[16] gridExtra_2.0.0      cluster_2.0.3        stringr_1.0.0
[19] locfit_1.5-9.1       nnet_7.3-11          grid_3.2.2
[22] AnnotationDbi_1.32.0 XML_3.98-1.3         survival_2.38-3
[25] BiocParallel_1.4.0   foreign_0.8-66       latticeExtra_0.6-26
[28] Formula_1.2-1        geneplotter_1.48.0   reshape2_1.4.1
[31] lambda.r_1.1.7       magrittr_1.5         scales_0.3.0
[34] Hmisc_3.17-0         MASS_7.3-44          splines_3.2.2
[37] xtable_1.7-4         colorspace_1.2-6     stringi_1.0-1
[40] acepack_1.3-3.3      munsell_0.4.2

hi Bruce,

After exploring ways to speed up the rlog, I came to prefer if users use the varianceStabilizingTransformation for datasets with many (e.g. 100s) of samples. The rlog has nice properties that we show in the paper, but it does require fitting a parameter for each sample. The 'fast' rlog was an approximation I was working on, but I came to think that the VST is preferable. The VST is just applying a function to the matrix of counts, so it's even faster. The only bottleneck with VST is estimating the dispersion trend (which the rlog also required). If you've already estimated dispersion (after DESeq() for example), you can use:

vsd <- varianceStabilizingTransformation(dds, blind=FALSE)
plotPCA(vsd)

which should take less than a second to return.

I have a fast routine for estimating the dispersion trend, which I will probably incorporate into a function at some point have now added to the devel branch as a function called vst() as of February 2016.