Dear professor, I want to use limma to analyse a geo data GSE28739, which is a two c0lor array data, the page is https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi, for example you can see link https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM712034 and https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSM712035 , it is the same sample labeled by two colors, cy3 and cy5, and I see the value in gsm, it is not the same for the same gene, and in eac page it described as VALUE normalized log10 ratio Ch1/Ch2 (test/reference)
I tried to understand in the liima userguide, but due to my poor knowledge and failed
so should I treat GSM712035 GSM712034 as 2 samples and use for differential analysis just like code
geo_exp<-matrix(as.numeric(as.matrix(geo_exp)),nrow=nrow(geo_exp),dimnames=dimnames)
mat=impute.knn(geo_exp)
geo_data=mat$data
geo_data=avereps(geo_data)
class <- c(rep("R",30),rep("S",20)) # if like that, 30 resist and 20 senstive
design <- model.matrix(~0+factor(class))
colnames(design) <- c("R","S")
fit <- lmFit(geo_data,design)
cont.matrix<-makeContrasts(S-R,levels=design)
fit1 <- contrasts.fit(fit, cont.matrix)
fit1 <- eBayes(fit1)
allgene<-topTable(fit1,adjust='fdr',number=200000)
or should I do like other ways?
and I am curious about the analysis difference in one color and two color array data
thanks a lot
in the limma userguide, it has description like this
Now consider two-color microarray experiments in which a common reference has been used on all the arrays. If the same channel has been used for the common reference throughout the experiment, then the expression log-ratios may be analysed exactly as if they were log-expression values from a single channel experiment. In these cases, the design matrix can be formed as for a single channel experiment.
Direct two-color designs are those in which there is no common reference, but the RNA samples are instead compared directly by competitive hybridization on the same arrays. Direct two-color designs can be very ecient and powerful, but they require the most statistical knowledge to choose the appropriate design matrix.
the link https://www.ncbi.nlm.nih.gov/geo/geo2r/?acc=GSE28739 seems to be use the common reference
does the GSE28739 belong to which two color? thanks a lot, anyone can help？
anyone knows, thanks a lot