I offer rigorous, publication-ready transcriptomics analysis from raw count matrices to biological interpretation using DESeq2, WGCNA, and pathway enrichment tools in R and Python.
I offer:
- Differential Expression Analysis: DESeq2, limma, edgeR
- WGCNA: co-expression network construction, hub gene identification, trait correlation
- Pathway Enrichment: GO, KEGG, Reactome using clusterProfiler
- ssGSEA: immune cell infiltration and gene set scoring
- GEO Dataset Handling: data retrieval, preprocessing, normalization
- Visualization: volcano plots, heatmaps, PCA, pheatmap, ggplot2
- Integration with drug discovery or network pharmacology pipelines
Skills:
- R · DESeq2 · WGCNA · limma · clusterProfiler · ggplot2 · pheatmap
- Python · pandas · matplotlib · seaborn
- GEO · TCGA · KEGG · Reactome · GO
Why choose me:
- Hands-on experience with real COPD and cancer transcriptomics datasets
- Clean, annotated R scripts delivered with every order
- Figures formatted to journal submission standards
- Responsive and detail-oriented throughout the project
- Comfortable handling messy, real-world GEO datasets