Bioinformatics scientist | NGS data analysis | clinical & cancer genomics
I work at the intersection of the sequencing lab and the command line. I've analyzed clinical NGS data for oncology and hematology testing in a CLIA/CAP lab, and I build reproducible pipelines for variant calling, RNA-seq and metagenomics.
- Currently: Molecular Geneticist, analyzing NGS data (Illumina DRAGEN, BaseSpace, Cell Ranger) for solid-tumor, liquid-biopsy and bone-marrow testing
- M.S. Biomedical Engineering (Gannon University) · M.Sc. Genetics (Osmania University)
- Open to relocation to California
| Project | What it does | Stack |
|---|---|---|
| germline-variant-calling-nf | FASTQ → annotated VCF, following GATK best practices, with ClinVar lookup. Benchmarked on GIAB NA12878: SNV F1 0.996, indel F1 0.994 | Nextflow, BWA-MEM, GATK4, bcftools, Docker, GitHub Actions |
| rnaseq-differential-expression-nf | Paired tumour-vs-normal colorectal RNA-seq: Salmon → DESeq2 → GSEA (MSigDB Hallmark) | Nextflow, Salmon, R/Bioconductor (DESeq2, fgsea) |
| crc-microbiome-biomarkers | 1,104 gut metagenomes from 8 countries: meta-analysis of CRC-associated bacteria and a Random Forest validated on held-out cohorts (AUC 0.80 CV, 0.78 cross-cohort) | Python, scikit-learn, SHAP, statsmodels |
Python R Bash Nextflow Git Docker conda · BWA GATK samtools bcftools Salmon DESeq2 fgsea · pandas scikit-learn SHAP · Illumina DRAGEN BaseSpace Cell Ranger · ClinVar GIAB NCBI BLAST
Contact: radandiswetcha@gmail.com · LinkedIn