Genomics Analysis

Genomics Analysis in R

Overview

Comprehensive genomics and bioinformatics statistical methods using Bioconductor packages. Covers differential expression analysis, pathway enrichment, and visualization for RNA-seq and microarray data.

Bioconductor Setup

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

# Install packages
BiocManager::install(c(
  "DESeq2",
  "edgeR",
  "limma",
  "clusterProfiler",
  "org.Hs.eg.db",
  "EnhancedVolcano",
  "ComplexHeatmap"
))

RNA-seq Differential Expression

DESeq2 Analysis

library(DESeq2)

# Create DESeqDataSet from count matrix
dds = 10) >= min_samples
dds  1)

DESeq2 with Multiple Factors

# Multi-factor design
dds  1))

# Convert to Entrez IDs
gene_ids  200 &
                              nFeature_RNA < 5000 &
                              percent.mt < 20)

# Normalize
seurat_obj <- NormalizeData(seurat_obj)
seurat_obj <- FindVariableFeatures(seurat_obj, nfeatures = 2000)

# Scale and PCA
seurat_obj <- ScaleData(seurat_obj)
seurat_obj <- RunPCA(seurat_obj)

# Clustering
seurat_obj <- FindNeighbors(seurat_obj, dims = 1:20)
seurat_obj <- FindClusters(seurat_obj, resolution = 0.5)

# UMAP
seurat_obj <- RunUMAP(seurat_obj, dims = 1:20)
DimPlot(seurat_obj, reduction = "umap")

# Find markers
markers <- FindAllMarkers(seurat_obj, only.pos = TRUE)

GWAS Analysis

Basic Association Testing

# Simple association test
gwas_results <- apply(genotype_matrix, 2, function(snp) {
  fit <- glm(phenotype ~ snp + covariates, family = binomial)
  summary(fit)$coefficients["snp", ]
})

# Manhattan plot
library(qqman)
manhattan(gwas_results, chr = "CHR", bp = "BP", p = "P", snp = "SNP")
qq(gwas_results$P)

Key Packages Summary

| Package | Purpose | |---------|---------| | DESeq2 | RNA-seq differential expression | | edgeR | RNA-seq analysis | | limma | Microarray and RNA-seq | | clusterProfiler | Pathway analysis | | EnhancedVolcano | Volcano plots | | ComplexHeatmap | Advanced heatmaps | | Seurat | Single-cell RNA-seq | | sva | Batch correction | | qqman | GWAS visualization |

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: choxos
• Source: choxos/BiostatAgent
• License: MIT

Install and usage instructions live in the source repository linked above.