Genomics & Bioinformatics Analysis

关于

This skill provides a structured framework for conducting advanced genomic research, offering standardized workflows for differential expression analysis, single-cell RNA-seq, and pathway enrichment. It leverages industry-standard Bioconductor packages such as DESeq2, Seurat, and clusterProfiler to help researchers move from raw count matrices to biological insights. Whether you are performing GWAS, correcting for batch effects with ComBat, or generating publication-ready visualizations like volcano plots and complex heatmaps, this skill provides the implementation patterns needed for rigorous bioinformatic pipelines.

主要功能

• Single-cell RNA-seq workflows including clustering and UMAP with Seurat
• Microarray preprocessing and batch effect correction techniques
• Functional enrichment analysis for GO, KEGG, and Gene Set Enrichment (GSEA)
• Differential expression analysis using DESeq2, edgeR, and limma-voom
• Publication-quality visualization for heatmaps, volcano plots, and PCA
• 0 GitHub stars

使用场景

• Identifying biomarkers and differentially expressed genes in RNA-seq studies
• Analyzing cell-type specific expression patterns in single-cell datasets
• Interpreting biological pathways and gene ontologies from experimental results