[BioC] combat error message

[Natasha [guest]]

Dear List,

I have a microarray dataset with 30 samples which I have normalised using the vsn function.

>From this data, clustering and PCA plots show that I appear to have chip and batch effects which I would like to account for using combat. However, when I try to account  for the batch effect, I get an error that I do not follow.

The code I have used is below:
=========
> chip
# 1 2 2 3 1 3 3 2 3 2 3 1 2 2 1 2 3 1 3 1 3 1 2 3 3 1 1 1 3 2
> group
# a_Cont   a_Cont   a_Cont   a_1 a_1 a_1 a_2 a_2 a_2 a_3 a_3 a_3 a_4   a_4   a_4   b_Cont b_Cont  b_Cont   b_1  b_1  b_1  b_2  b_2  b_2  b_3  b_3  b_3  b_4    b_4    b_4    
# Levels: a_Cont a_1 a_2 a_3 a_4 b_Cont b_1 b_2 b_3 b_4
> mod = model.matrix(~as.factor(group))

> combat.c = ComBat(dat=d.norm, batch=chip, mod=mod, numCovs=NULL, par.prior=TRUE, prior.plots=FALSE)
# Found 3 batches
# Found 9  categorical covariate(s)
# Standardizing Data across genes
# Fitting L/S model and finding priors
# Finding parametric adjustments
# Adjusting the Data

### Combat to get rid of batch effect
> day2
 # 1 2 3 1 2 3 1 2 3 1 2 3 1 2 3 4 4 5 4 4 5 4 4 5 4 4 5 4 4 5
>mod #same as above

> combat.b = ComBat(dat=combat.c, batch=day2, mod=mod, numCovs=NULL, par.prior=TRUE, prior.plots=FALSE)
# Found 5 batches
# Found 9  categorical covariate(s)
# Standardizing Data across genes
####### Error in solve.default(t(design) %*% design) : 
#######   system is computationally singular: reciprocal condition number = 7.93016e-18 
=========

Any help much appreciated. 
(I do know that the R /BioC version is not the latest, but hoping that is not the case here!)

Many Thanks,
Natasha

 -- output of sessionInfo(): 

sessionInfo()
# R version 3.0.2 (2013-09-25)
# Platform: x86_64-apple-darwin10.8.0 (64-bit)
# 
# locale:
#   [1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
# 
# attached base packages:
#   [1] parallel  stats     graphics  grDevices utils     datasets  methods   base     
# 
# other attached packages:
#   [1] gplots_2.13.0         WriteXLS_3.5.0        limma_3.18.13         genefilter_1.44.0     sva_3.8.0             mgcv_1.7-29           nlme_3.1-117          corpcor_1.6.6        
# [9] ClassDiscovery_2.14.1 PreProcess_2.12.3     oompaBase_3.0.0       mclust_4.3            cluster_1.15.2        scatterplot3d_0.3-35  gdata_2.13.3          vsn_3.30.0           
# [17] Biobase_2.22.0        BiocGenerics_0.8.0   
# 
# loaded via a namespace (and not attached):
#   [1] affy_1.40.0           affyio_1.30.0         annotate_1.40.1       AnnotationDbi_1.24.0  BiocInstaller_1.12.1  bitops_1.0-6          caTools_1.17          DBI_0.2-7            
# [9] grid_3.0.2            gtools_3.4.0          IRanges_1.20.7        KernSmooth_2.23-12    lattice_0.20-29       Matrix_1.1-3          preprocessCore_1.24.0 RSQLite_0.11.4       
# [17] splines_3.0.2         stats4_3.0.2          survival_2.37-7       tools_3.0.2           XML_3.95-0.2          xtable_1.7-3          zlibbioc_1.8.0  


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