I am trying to execute this GEO2R script in RStudio version 4.0.

#   Differential expression analysis with limma
library(Biobase)
library(GEOquery)
library(limma)

# load series and platform data from GEO
gset <- getGEO("GSE89333", 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 <- "0011"
sml <- c()
for (i in 1:nchar(gsms)) { sml[i] <- substr(gsms,i,i) }

# log2 transform
ex <- exprs(gset)
qx <- as.numeric(quantile(ex, c(0., 0.25, 0.5, 0.75, 0.99, 1.0), na.rm=T))
LogC <- (qx[5] > 100) ||
          (qx[6]-qx[1] > 50 && qx[2] > 0) ||
          (qx[2] > 0 && qx[2] < 1 && qx[4] > 1 && qx[4] < 2)
if (LogC) { ex[which(ex <= 0)] <- NaN
  exprs(gset) <- log2(ex) }

# set up the data and proceed with analysis
sml <- paste("G", sml, sep="")    # set group names
fl <- as.factor(sml)
gset$description <- fl

# Create the study design
design <- model.matrix(~ description + 0, gset)
colnames(design) <- levels(fl)

# Fit the linear model on the study's data
fit <- lmFit(gset, design)

# Make individual contrasts
cont.matrix <- makeContrasts(G1-G0, levels=design)
fit2 <- contrasts.fit(fit, cont.matrix)

# Applying the empirical Bayes method to the fitted values
# Acts as an extra normalisation step and aims to bring the different probe-wise variances to common values
fit2 <- eBayes(fit2, 0.01)
tT <- topTable(fit2, adjust="fdr", sort.by="B", number=250)

tT <- subset(tT, select=c("ID","Gene.symbol","logFC"))
write.table(tT, file=stdout(), row.names=F, sep="\t")

But it is giving me error in gsms (group samples) when I am running the script with different microarray platforms. How can i exclude this step? Please help me