[BioC] how to handle technical replicates and biological replicates
using limma
Ren Na
na at uthscsa.edu
Wed Aug 11 00:37:49 CEST 2004
Dr. Gordon Smyth,
Thank you for answering my question.
I still have some questions about how to fit mouse effect for my data,
My purpose is to find significantly expressed genes between mutant and
wild type mice. I tried to figure it out by reading "Limma user's guide"
and came up with the following solution, is it right? or doesn't make
any sense?
My targets file is:
SlideNumber FileName Cy3 Cy5 Target1 Target2
1 1391.spot wt1 mu1 wt1
mu1
2 1392.spot mu1 wt1 mu1
wt1
3 1340.spot wt2 mu1 wt2
mu1
4 1341.spot mu1 wt2 mu1
wt2
5 1395.spot wt3 mu1 wt3
mu1
6 1396.spot mu1 wt3 mu1
wt3
7 1393.spot wt1 mu2 wt1
mu2
8 1394.spot mu2 wt1 mu2
wt1
9 1371.spot wt2 mu2 wt2
mu2
10 1372.spot mu2 wt2 mu2
wt2
11 1338.spot wt3 mu2 wt3
mu2
12 1339.spot mu2 wt3 mu2
wt3
13 1387.spot wt1 mu3 wt1
mu3
14 1388.spot mu3 wt1 mu3
wt1
15 1399.spot wt2 mu3 wt2
mu3
16 1390.spot mu3 wt2 mu3
wt2
17 1397.spot wt3 mu3 wt3
mu3
18 1398.spot mu3 wt3 mu3
wt3
mu1, mu2, and mu3 are different mice which are biological replicates,
and wt1, wt2 and wt3 are different mice which are biological replicates.
> targets <- readTargets()
# I try to include mouse effect in the following way:
> t1 <- model.matrix(~0+factor(targets$Target1))
> t2 <- model.matrix(~0+factor(targets$Target2))
> t3 <- t1+t2
> design <- cbind(Dye=1,
MuvsWt=c(1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1), t3 )
> pair <- c(1,1,2,2,3,3,4,4,5,5,6,6,7,7,8,8,9,9)
> corfit <- duplicateCorrelation(MA,design,block=pair)
> fit <- lmFit(MA,design,block=pair,correlation=corfit$consensus)
> fit <- eBayes(fit)
Thanks again for your time.
Ren
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