Dear all,

I have this situation for a gene overexppressed:

Group A: average 85.33

GroupB: average 23081.19

average gene 1930.54

On the result table  of differential expression:

basemean: 1930.54,log2Foldchange 5.115 lfcSE 0.341

The results seem more different from  the ratio obtained.. 

I found this results also in other comparison:

Any idea?

R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.2 LTS

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C               LC_TIME=it_IT.UTF-8       
 [4] LC_COLLATE=en_US.UTF-8     LC_MONETARY=it_IT.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=it_IT.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
[10] LC_TELEPHONE=C             LC_MEASUREMENT=it_IT.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
 [1] gplots_3.0.1               genefilter_1.54.2          limma_3.28.21             
 [4] biomaRt_2.28.0             reshape2_1.4.2             RColorBrewer_1.1-2        
 [7] ggplot2_2.2.1              pheatmap_1.0.8             DESeq2_1.12.4             
[10] SummarizedExperiment_1.2.3 Biobase_2.32.0             GenomicRanges_1.24.3      
[13] GenomeInfoDb_1.8.7         IRanges_2.6.1              S4Vectors_0.10.3          
[16] BiocGenerics_0.18.0       

loaded via a namespace (and not attached):
 [1] gtools_3.5.0         locfit_1.5-9.1       splines_3.3.2        lattice_0.20-35     
 [5] colorspace_1.3-2     htmltools_0.3.5      base64enc_0.1-3      survival_2.40-1     
 [9] XML_3.98-1.5         foreign_0.8-67       DBI_0.6-1            BiocParallel_1.6.6  
[13] plyr_1.8.4           stringr_1.2.0        zlibbioc_1.18.0      munsell_0.4.3       
[17] gtable_0.2.0         caTools_1.17.1       htmlwidgets_0.8      memoise_1.0.0       
[21] labeling_0.3         latticeExtra_0.6-28  knitr_1.15.1         geneplotter_1.50.0  
[25] AnnotationDbi_1.34.4 htmlTable_1.9        Rcpp_0.12.9          KernSmooth_2.23-15  
[29] acepack_1.4.1        xtable_1.8-2         backports_1.0.5      scales_0.4.1        
[33] checkmate_1.8.2      gdata_2.17.0         Hmisc_4.0-2          annotate_1.50.1     
[37] XVector_0.12.1       gridExtra_2.2.1      digest_0.6.12        stringi_1.1.2       
[41] grid_3.3.2           tools_3.3.2          bitops_1.0-6         magrittr_1.5        
[45] lazyeval_0.2.0       RCurl_1.95-4.8       tibble_1.2           RSQLite_1.1-2       
[49] Formula_1.2-1        cluster_2.0.6        Matrix_1.2-8         data.table_1.10.0   
[53] assertthat_0.1       rpart_4.1-10         nnet_7.3-12        

If you used the latest version 1.16 you would get an MLE fold change. You can set betaPrior=FALSE to get an MLE fold change with older versions.