[BioC] lumi - construct a design matrix

[Paolo Kunderfranco]

Dear All,
I am wondering about the construction of a design matrix for identify
diff erentially expressed genes with Lumi package.
I am asking this beacause I obtain strange results when i compare
between groups.

I have 4 sample, each one in triplicate.
I substracted bkg, normalized and vst transformed.


dataMatrix <- exprs(lumi.N.Q)
presentCount <- detectionCall(x.lumi)
selDataMatrix <- dataMatrix[presentCount > 1,]
probeList <- rownames(selDataMatrix)



sampleType <- c('CME','ES','CMA','CMN','CME','ES','CMA','CMN','CME','ES','CMA','CMN')
design <- model.matrix(~ factor(sampleType))
colnames(design) <- c('CME','ES','CMA','CMN')


fit1 <- lmFit(selDataMatrix, design)
constrast.matrix <- makeContrasts (ES-CMN,ES-CME,ES-CMA,levels=design)
fit1_2 <- contrasts.fit(fit1,constrast.matrix)
fit1_2 <- eBayes(fit1_2)



If now I try to check how the matrix is designed:

design()

CME ES CMA CMN
1    1  1   0   0
2    1  0   0   1
3    1  0   0   0
4    1  0   1   0
5    1  1   0   0
6    1  0   0   1
7    1  0   0   0
8    1  0   1   0
9    1  1   0   0
10   1  0   0   1
11   1  0   0   0
12   1  0   1   0
attr(,"assign")
[1] 0 1 1 1
attr(,"contrasts")
attr(,"contrasts")$`factor(sampleType)`
[1] "contr.treatment"


and this seems not be the one I designed,  where am I wrong?


Thanks,
Paolo


ssionInfo()
R version 2.15.0 (2012-03-30)
Platform: i386-pc-mingw32/i386 (32-bit)

locale:
[1] LC_COLLATE=Italian_Italy.1252  LC_CTYPE=Italian_Italy.1252
LC_MONETARY=Italian_Italy.1252
[4] LC_NUMERIC=C                   LC_TIME=Italian_Italy.1252

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

other attached packages:
 [1] annotate_1.34.1           lumiMouseAll.db_1.18.0
org.Mm.eg.db_2.7.1        limma_3.12.1
 [5] lumiMouseIDMapping_1.10.0 RSQLite_0.11.1            DBI_0.2-5
            AnnotationDbi_1.18.1
 [9] lumi_2.8.0                nleqslv_1.9.3
methylumi_2.2.0           ggplot2_0.9.1
[13] reshape2_1.2.1            scales_0.2.1
Biobase_2.16.0            BiocGenerics_0.2.0

loaded via a namespace (and not attached):
 [1] affy_1.34.0           affyio_1.24.0         bigmemory_4.2.11
BiocInstaller_1.4.7
 [5] Biostrings_2.24.1     bitops_1.0-4.1        BSgenome_1.24.0
colorspace_1.1-1
 [9] dichromat_1.2-4       digest_0.5.2          DNAcopy_1.30.0
GenomicRanges_1.8.7
[13] genoset_1.6.0         grid_2.15.0           hdrcde_2.16
IRanges_1.14.4
[17] KernSmooth_2.23-8     labeling_0.1          lattice_0.20-6
MASS_7.3-19
[21] Matrix_1.0-7          memoise_0.1           mgcv_1.7-18
munsell_0.3
[25] nlme_3.1-104          plyr_1.7.1            preprocessCore_1.18.0
proto_0.3-9.2
[29] RColorBrewer_1.0-5    RCurl_1.91-1.1        Rsamtools_1.8.5
rtracklayer_1.16.2
[33] stats4_2.15.0         stringr_0.6           tools_2.15.0
XML_3.9-4.1
[37] xtable_1.7-0          zlibbioc_1.2.0
>