| FazBrowse GitHub Viewer | Trending | | Home |
| Tools: [Original HTTPS Page] |
Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.
You must be logged in to block users.
Contact GitHub support about this userβs behavior. Learn more about reporting abuse.
Report abuseBioinformatics Data Scientist & Researcher | Data Pipelines & Agentic AI | Transcriptomics & Genomics
Welcome to my page! I am a Bioinformatician who has been drawing actionable insights for Drug Development and Clinical studies within Cancer and Cardio-metabolic disease areas from Transcriptomics and Genomics data, ever since I first discovered Bioinformatics in 2018. This GitHub showcases repositories spanning my areas of expertise, including standard Transcriptomics and Genomics analyses, Data Pipelines and Agentic AI tools that I am developing.
Recreates bulk RNAseq analyses conducted as part of my PKP2 Gene Therapy for ARVC study published within Communications Medicine in 2024.
GWAS meta-analysis of metabolites and T2D; includes harmonization, genetic correlation, fine-mapping, eQTL colocalization, and Mendelian randomization.
LangGraph-based agentic workflow that parses Genomics sequencing Quality Control (QC) metrics and uses an LLM to generate plain-English summaries for non-computational research collaborators.
Transcriptomic analysis pipeline for single-cell RNA sequencing data. Quality control, clustering, differential expression, and cell-type annotation.
GitHub @scatcher125 | LinkedIn | Google Scholar
Recreates bulk RNAseq analyses conducted as part of my PKP2 Gene Therapy for ARVC study published within Communications Medicine in 2024.
R
GWAS meta-analysis of metabolites and T2D; includes harmonization, genetic correlation, fine-mapping, eQTL colocalization, and Mendelian randomization.
LangGraph-based agentic workflow that parses Genomics sequencing Quality Control (QC) metrics and uses an LLM to generate plain-English summaries for non-computational research collaborators.
Python
Single cell RNAseq analysis using Seurat. Includes dimensionality reduction, clustering and cell type identification.
R
Bulk RNA-seq analysis including differential gene expression, gene set enrichment analysis, and weighted gene co-expression network analysis.
R
Interactive application to explore various ecological diversity metrics
| Back | FazBrowse Home | New Git URL |