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Key Distinctions

Carefully defining your categorical boundaries ensures clarity in analysis, interpretation, and reproducibility. This section should surface how you’re drawing scientific lines and the implications of those choices.

Core Categories

  • What major distinctions are you drawing?
    • Example: Case vs. control; affected vs. unaffected carriers; treated vs. untreated
    • Example: Driver variants vs. modifier variants; coding vs. regulatory elements
    • Example: Early-onset vs. late-onset cases; cell type A vs. cell type B

In-Scope (as of YYYY-MM-DD)

  • What’s currently included in your study’s scope?
    • Example: BMPR2 mutation carriers sequenced with >30x WGS
    • Example: Variants in genes with immune pathway annotation in GO or KEGG
    • Example: Bulk RNA-seq from patient-derived fibroblasts in untreated state

Out-of-Scope (as of YYYY-MM-DD)

  • What is currently excluded, and why?
    • Example: Pediatric samples due to consent restrictions
    • Example: Functional assays requiring CRISPR validation
    • Example: Single-cell resolution analysis (to be reserved for future aims)

Risks of Current Boundaries

  • What are the analytical, ethical, or interpretive risks of the distinctions you’re drawing?
    • Example: Bias due to uneven population sampling across case/control
    • Example: Risk of excluding informative rare variants by current filter thresholds
    • Example: Potential misclassification of modifiers as noise due to lack of phenotypic resolution