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

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