Start Here

Purpose: This field guide documents considerations for building a biomarker discovery pipeline from RNA-seq meta-analysis, with emphasis on lessons learned, reproducibility, and practical recommendations for researchers working with noisy multi-study omics data.

Grant mission: Developing molecular resilience biomarkers to support selective breeding and management of shellfish aquaculture under disease pressure. (Full narrative: ProjectSummaryandNarrative.pdf)

What was done: Integrated RNA-seq datasets from Crassostrea virginica exposed to Perkinsus marinus, conducted differential abundance analyses across multiple independent studies, and developed a two-step classifier pipeline that identifies reproducible gene expression signatures.

Key results: Identified a validated 6-gene classifier panel that distinguishes tolerant from sensitive oyster phenotypes, confirmed via Leave-One-Study-Out (LOSO) cross-validation.

Intended application: This guide is a reusable template for researchers facing batch effects, weak signals, and overfitting risks in multi-study biomarker discovery.

---

Developed by Shelly Wanamaker and Steve Yost with AI assistance. Cite as: Wanamaker, S.A. and Yost, S. (2025). Resilience Biomarkers Field Guide. https://resilience-biomarkers-for-aquaculture.github.io/field-guide/