[R] RNA Seq Analysis in R

Anas Jamshed @n@@j@m@hed1994 @end|ng |rom gm@||@com
Sat Aug 1 13:01:08 CEST 2020


I choose microarray data GSE75693 of 30 patients with stable kidney
transplantation and 15 with BKVN to identify differentially expressed genes
(DEGs). I performed this in GEO2R and find R script there and Runs R script
Successfully on R studio as well. The R script is :

 # Differential expression analysis with limma

library(Biobase)
library(GEOquery)
library(limma)
# load series and platform data from GEO

gset <- getGEO("GSE75693", GSEMatrix =TRUE, AnnotGPL=TRUE)if
(length(gset) > 1) idx <- grep("GPL570", attr(gset, "names")) else idx
<- 1
gset <- gset[[idx]]
# make proper column names to match toptable
fvarLabels(gset) <- make.names(fvarLabels(gset))
# group names for all samples
gsms <- paste0("000000000000000000000000000000XXXXXXXXXXXXXXX11111",
        "1111111111XXXXXXXXXXXXXXXXXXX")
sml <- c()for (i in 1:nchar(gsms)) { sml[i] <- substr(gsms,i,i) }
# eliminate samples marked as "X"
sel <- which(sml != "X")
sml <- sml[sel]
gset <- gset[ ,sel]
# log2 transform
exprs(gset) <- log2(exprs(gset))
# set up the data and proceed with analysis
sml <- paste("G", sml, sep="")    # set group names
fl <- as.factor(sml)
gset$description <- fl
design <- model.matrix(~ description + 0, gset)
colnames(design) <- levels(fl)
fit <- lmFit(gset, design)
cont.matrix <- makeContrasts(G1-G0, levels=design)
fit2 <- contrasts.fit(fit, cont.matrix)
fit2 <- eBayes(fit2, 0.01)
tT <- topTable(fit2, adjust="fdr", sort.by="B", number=1250)

tT <- subset(tT,
select=c("ID","adj.P.Val","P.Value","t","B","logFC","Gene.symbol","Gene.title"))
DEGs = subset(tT, P.Value < 0.01 & abs(logFC) > 2)

After running this no genes are found plz help me

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