SHRUTI SAHU

I'm currently contributing to GNEConnect at the Tata Institute for Genetics and Society (TIGS), supporting workflow design, data structuring, documentation, and REDCap-based electronic data capture for a secure GNE Myopathy patient registry.

I designed an end-to-end, Nextflow-orchestrated RNA-seq differential gene expression pipeline for an HGPS/Progeria dataset, covering FastQC, MultiQC, Cutadapt, STAR, featureCounts, and edgeR. I'm also building a drug-repurposing workflow that combines LINCS signature concordance, chemical similarity filtering, docking, and machine-learning consensus scoring.

For my master's thesis at IBAB, I built a harmonized R pipeline for cross-disease bulk RNA-seq analysis across 202 whole-blood samples from Parkinson's, Huntington's, and coronary artery disease cohorts. I used DESeq2, limma-voom, ComBat, and clusterProfiler to identify conserved biological signatures.

I've also worked on single-cell RNA-seq analysis with Scanpy, GATK4-based WES variant calling benchmarked against GIAB/NA12878 truth sets, and structural bioinformatics workflows using AlphaFold2, PyMOL, and KNIME. I'm seeking a Bioinformatics Engineer role in Bengaluru where I can build scalable, reproducible genomics workflows.