Dipti Gulumbe

I am a Bioinformatics Scientist currently working at Chromosome Labs Pvt. Ltd., specializing in the computational analysis of multi-omics data to derive meaningful biological insights. My expertise spans next-generation sequencing (NGS), cancer genomics, GWAS, metagenomics, structural bioinformatics, and computational drug discovery.I have hands-on experience in managing end-to-end NGS workflows—from raw sequencing reads to final reports—by designing, optimizing, and automating scalable pipelines. My core work includes quality control (FastQC, MultiQC, fastp), alignment (BWA, HISAT2, STAR), variant calling (GATK, SAMtools, FreeBayes), transcriptomics analysis (DESeq2, edgeR), and functional annotation (ANNOVAR, VEP). I am proficient in handling both bulk and RNA-seq data, ensuring accuracy, reproducibility, and efficiency in analysis.

At Chromosome Labs Pvt. Ltd., I am actively involved in building and maintaining robust bioinformatics pipelines, improving turnaround time, and supporting clinical/research projects with high-quality data interpretation. Previously, at SMCS-PSI Data Analytics, I developed automated variant calling pipelines that reduced processing time by over 60%.

In addition, I contribute to computational drug discovery through large-scale molecular docking studies (20,000+ ligands across multiple targets) and apply molecular simulation techniques. I also create publication-ready visualizations using R (Bioconductor, ggplot2, ComplexHeatmap) and Python (pandas, matplotlib, seaborn).

Key Skills:

• NGS Data Analysis (WGS, WES, RNA-seq, Metagenomics)

• Pipeline Development & Automation (Bash, Python, Nextflow, Snakemake)

• Variant Calling & Annotation (GATK, ANNOVAR, VEP)

• Transcriptomics & Differential Expression Analysis (DESeq2, edgeR)

• Genomic Data Handling (BEDTools, SAMtools, bcftools)

• Cloud & HPC Computing (Linux, cluster environments)

• Data Visualization (R, Bioconductor, Python)

• Molecular Docking & Simulation (AutoDock, Schrödinger tools)

• Machine Learning & AI applications in Bioinformatics

• Reproducible Research & Workflow Optimization

I am passionate about advancing bioinformatics through innovative approaches, automation, and the integration of AI/ML to solve complex biological problems and deliver impactful, data-driven solutions.