[BioC] Nested Design (Again) & Subset WithinArray Correlation
Y. Osee Sanogo
sanogo at illinois.edu
Tue Jul 27 08:09:45 CEST 2010
Hello,
I have two questions which may be really trivial...but since I am stuck, I’ll
appreciate any help.
Question 1: Nested design: This has been addressed before, but I am just not
sure whether I am doing it right. The experiment consisted of two groups of
fishes (treated and not treated) with three tanks in each group. Each tank
hosted three fishes (total =18) of those fishes n=10 (5 per treatment group)
were selected for microarray (Notice unequal number of fishes per tank!).
I am interested in 1) Treatment effect (individual fishes)
2) Treatment effect (fishes nested within tanks, i.e. Need to
average the gene expression of fishes within each tank )
3) Whether there is tank effect
I have tried the following design based upon what I found online, but was not
really sure whether this is the right way of doing it.
#ExpressionSet =ES_Filt
#targets= “phenoData3.txt”: ATTACHED
design.nested_ES<- model.matrix(~Key + (tank/Fish), data=targets)
colnames(design.nested_ES)
#I am getting many contrasts, and I am not sure which one represents
“tank/Fish”
fit.nested_ES <- lmFit(ES_Filt, design.nested_ES)
Fit.nested_ES <- eBayes(fit.nested_ES)
Pred2_Nested_ES<-topTable(Fit.nested_ES, coef=2, adjust="BH", n=Inf)
Pred2_Nested_ES[1:10,]
I will really appreciate your help.
Question 2: Testing Subset of Within array “replicates” with different gene
names. I have a subset of “overlapping’ gene list [ATTACHED] =
”Unique_gene2transcripts.xls” and I would like to see how they correlate to
assess the hybridization efficiency on the chip. The sequences and the probes
are not identical, but overlap significantly. From reading the postings, I know I
can’t use ‘duplicaleCorrelation, because the probes are randomly scattered on
the array and I was not sure about how to use “avedups” in a subset of genes
with different names.
Thank you so much and my apologies if this has been solved before (You can
point me to the discussion).
Cheers,
Osee
Thank you.
Osee
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