# Bioconductor has a mission of “promot[ing] the statistical 
# analysis and comprehension of current and emerging high-throughput 
# biological assays.” 


# Install Bioconductor
if (!require("BiocManager", quietly = TRUE))
  install.packages("BiocManager")
BiocManager::install()

# Install edgeR as an example
BiocManager::install("edgeR")

# Load edgeR
library(edgeR)

# Example: Create a DGEList object for RNA-seq data
counts <- matrix(rpois(100, lambda = 10), ncol = 5)
group <- factor(c("Control", "Control", "Treatment", "Treatment", "Treatment"))
dge <- DGEList(counts = counts, group = group)

# str() function can be used to inspect the structure of the object
str(dge)

# Normalize counts using TMM normalization
dge <- calcNormFactors(dge)
print(dge)

# Perform differential expression analysis
dge <- estimateDisp(dge)
fit <- glmFit(dge, design = model.matrix(~group))
lrt <- glmLRT(fit, coef = 2) # Genewise Likelihood Ratio Tests
topTags(lrt)