Wednesday, March 25, 2026, 1-3 p.m., Online
Taught by Srilakshmi Chaparala and Alexis Cenname
Register for Chat to Code in R: Bulk RNA-Seq in Google Colab with Generative AI
Turn plain‑English prompts into reproducible R code as we walk through the key steps of a bulk RNA‑seq analysis—no prior coding knowledge required. In this hands-on session, you’ll start with raw RNA-seq count data downloaded from a GEO-deposited study and work through quality control, differential expression between two conditions (using DESeq2 and edgeR), publication-ready visualizations (volcano plots, heatmaps, MA plots), and functional enrichment to interpret pathways and biology. The core of the workshop is a chat-based, prompt-driven workflow: you’ll learn how to describe your intent in natural language and have R code generated for you, then run, refine, and document it using Google Colab. Along the way, we’ll cover data upload, environment setup, effective prompt writing, and result interpretation.
- Summarize the bulk RNA‑seq analysis pipeline (raw count data → QC/PCA → DEGs → enrichment) and define key concepts (normalization, dispersion, multiple testing, contrasts)
- Formulate effective chat-based prompts using Google Gemini to generate R code for RNA-seq data analysis workflow
- Perform differential expression with DESeq2 and edgeR, and compare outputs (e.g., DEG counts, log2FC, adjusted p‑values
- Assemble a reproducible Colab notebook that documents prompts, generated R code, and results (DEG tables, plots, enrichment summaries), suitable for reuse and reporting.