Context:      Understanding relationships between genetic variation and clinical phenotypes requires tools that support flexible, exploratory analysis.

 

Data:            ClinVar, GWAS summary data, Ensembl and RefSeq annotations.

 

Methods:    R, tidyverse, ggplot2, ggplotly, reproducible preprocessing pipelines.

 

Outcome:    An interactive analytical workflow and Shiny application enabling dynamic exploration of variant distributions, phenotypic associations, and gene-level summaries.

* Although CTLA4 and MYO9B intersect within shared immune pathways, the genetic signals observed here suggest divergent mechanisms underlying similar gastrointestinal outcomes.