[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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