Dear Bioconductors, I have a question related to estimates of microarray expression fold change after using vst in lumi (as the authors recommend) rather than a simple log2 transformation. I apologise if this is a foolish question or if my google-fu was too weak to find the answer when I searched. I am working with illumina sentrix expression data, using lumi's vst and quantile normalization, then limma to model differential expression. One of my collaborators has asked for the fold changes reported by limma (as log2FC) on a linear scale so he can check the top ones with qPCR. Initially, I was going to make the obvious suggest that he take 2^log2FC to transform what lumi reported as log2FC back to a linear scale - but this probably not the right transformation - because vst is not log2! To confirm this, I reran the analysis replacing the lumi vst option with a log2 transformation to see what differences there were. As can be seen from the small sample below, there were variations in gene ranking, differences in p values (vst gave smaller p values) and the values reported as 'log2FC' were vastly different. I understand that limma estimates "log2FC" as the difference between transformed intensity values - but how can they be interpreted if the data were transformed with vst rather than log2? I imagine that the vst results are 'better' because it's a better transformation than log2 but I am not sure how to explain this to my colleague - advice appreciated. Using vst (apologies for the formatting): ID geneSymbol logFC CI.025 CI.975 AveExpr t P.Value adj.P.Val B 5447 BJnZRnS5W.xQwHiYVQ EEF1A2 6.737470 6.577077 6.897863 10.133500 137.41304 2.694315e-70 7.260639e-66 147.7207 23109 rQlXje3RRE1fQVEa3k SLN 7.534754 7.345115 7.724392 10.666689 129.97466 5.361216e-69 7.223702e-65 145.1452 18091 leKDHioqXpx7d3kd54 MYBPC1 7.524289 7.322845 7.725733 10.609381 122.18770 1.481136e-67 1.330455e-63 142.2374 18134 K_W3elXdKe58XuEknc MYL3 7.076920 6.862857 7.290984 10.309408 108.14785 1.038158e-64 6.994069e-61 136.3602 18123 llE343nSV6K5SQJVOc MYH7 7.296190 7.070833 7.521547 10.494978 105.91110 3.185741e-64 1.716987e-60 135.3381 Using log2: ID geneSymbol logFC CI.025 CI.975 AveExpr t P.Value adj.P.Val B 5447 BJnZRnS5W.xQwHiYVQ EEF1A2 8.833916 8.552823 9.115010 9.164795 102.80600 8.505465e-67 2.292053e-62 139.7942 18134 K_W3elXdKe58XuEknc MYL3 9.145482 8.812582 9.478383 9.337462 89.86878 1.832162e-63 2.468655e-59 133.0097 18179 9X8dQtVHUZNfXRQdIk MYOZ1 8.509667 8.194560 8.824774 9.452997 88.34276 4.864153e-63 4.369306e-59 132.1303 23659 6Ij1VCKLt6Cje5ehLo SRL 6.949980 6.685096 7.214864 8.398941 85.83111 2.517144e-62 1.695800e-58 130.6422 24961 3IlVNOVFFR3pHp9Nfw TPM2 8.845876 8.502794 9.188958 8.828952 84.34499 6.808768e-62 3.669654e-58 129.7369 > sessionInfo() R version 2.14.1 (2011-12-22) Platform: x86_64-unknown-linux-gnu (64-bit) locale: [1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_AU.UTF-8 LC_COLLATE=en_AU.UTF-8 [5] LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8 [7] LC_PAPER=C LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] lumi_2.6.0 nleqslv_1.9.2 methylumi_2.0.4 Biobase_2.14.0 [5] limma_3.10.2 loaded via a namespace (and not attached): [1] affy_1.32.1 affyio_1.22.0 annotate_1.32.1 [4] AnnotationDbi_1.16.11 BiocInstaller_1.2.1 DBI_0.2-5 [7] grid_2.14.1 hdrcde_2.15 IRanges_1.12.5 [10] KernSmooth_2.23-7 lattice_0.20-0 MASS_7.3-16 [13] Matrix_1.0-3 mgcv_1.7-13 nlme_3.1-103 [16] preprocessCore_1.16.0 RSQLite_0.11.1 xtable_1.6-0 [19] zlibbioc_1.0.0 [[alternative HTML version deleted]]