# Load the DESeq2 library
library(DESeq2)

# Read your count data
counts <- read.csv("C:/Users/anant/OneDrive/Documents/RNASeq/count_data.csv", row.names = 1)

# Read the metadata
metadata <- read.csv("C:/Users/anant/OneDrive/Documents/RNASeq/Metadata.csv")

# Create a DESeqDataSet object with count data and metadata
dds <- DESeqDataSetFromMatrix(countData = counts, colData = metadata, design = ~ condition)

# Run the DESeq analysis
dds <- DESeq(dds)

# Get differentially expressed genes
res <- results(dds)
res <- res[order(res$padj),]

# Show the top differentially expressed genes
head(res)

This code works excedpt this one thing- Warning message:

In DESeqDataSet(se, design = design, ignoreRank) :
  some variables in design formula are characters, converting to factors

please confirm if this is right because I got this code from a site.