hello fellows ,
i am currently working on a project in which i have to do micro array analysis.I am working on R for analysis, my series have 10 samples and it is normalized so i directly applied limma code on that. The code is working but i am not satisfied with the result or with my code .kindly help me in the best possible way (code is given below).
q1> if the code i am using is correct to know DEGs from sample data
q2> as i write n=10 , for only 10 degs but as i understand my query is to know all the degs of sample for this i search on Google and i use n=Inf but when i used it, i got a huge list of probe list but no other info. e.g. entrez, symbol etc. So kindly tell me the specific code for knowing all the degs of my sample or we have to select genes manually a/c to need.
q3> as you can see in my result only 3 probes are showing p.adj.value < 0.05, so i have a confusion that from 10 samples i only work on 3 genes it will be not good for the further enrichment and miRna analysis i follow the same procedure for n=500 and i got 3 genes . So should i dont do the BH test and go further or is there is an alternative option for that.please help me out in the best possible way.
library(limma)
library(GEOquery)
gse <- getGEO("GSE*****", GSEMatrix = TRUE)
show(gse)
> gse <- gse[[1]]
> fData(gse) <- fData(gse)[,c(1,2,10:12)]
> grp <- factor(sapply(strsplit(as.character(pData(gse)[,1]), " "), "[", 1))
>grp
[1] A_set A_set AS_set AS_set AS_set F_set F_set S_set S_set S_set
Levels: A_set AS_set F_set S_set
> design <- model.matrix(~grp)
> fit <- lmFit(gse, design)
> fit2 <- eBayes(fit)
tt<- topTable(fit2, coef = 2, adjust = "fdr",n = 10)
ID GB_ACC
210004_at 210004_at AF035776
236646_at 236646_at BE301029
1560477_a_at 1560477_a_at AK054643
213227_at 213227_at BE879873
222221_x_at 222221_x_at AY007161
220922_s_at 220922_s_at NM_013453
222860_s_at 222860_s_at AB033832
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You cannot fit a linear model if you only have one sample per group, which is what the error is telling you. In the second case the error is pretty clear - your design matrix doesn't match your data, so you have mis-specified something.