SPARC CCF Multi-omics analysis
A pipeline to predict risk genes, implicated cell types and drugs for repurposing based on known risk genes (derived from GWAS) for complex traits.
Separating cell senescence from generic inflammation in IBD mucosa: SASP burden predicts biologic response (AUC 0.85/0.74); MR+coloc nominate CCL8 (risk) & CXCR2 (protective). Pure-Python, public-data pipeline.
All QC, annotation, and analyses for IBD exomes
R Shiny application for the multi-omics analysis of inflammatory bowel disease
Analysis code for the study Linkage analysis identifies novel genetic modifiers of microbiome traits in families with inflammatory bowel disease (Sharma et al., Gut Microbes, 2022).
PhD thesis on data integration on inflammatory bowel disease
Reproducible pipeline for structuring and de-identifying abdominal radiology reports for clinical NLP research
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