PRANAVA UPPARLAPALLI
Bioinformatics Analyst & Engineer specializing in spatial transcriptomics, single-cell analysis, and reproducible Nextflow pipeline development at HPC scale.
GitHub
Email
Skills & Expertise
Specializing in reproducible genomics analysis, spatial transcriptomics, machine learning for biological data, and production-ready pipelines across HPC and cloud systems.
Python
R
Nextflow
Docker
Git
Snakemake
NGS & Omics Data
End-to-end RNA-seq, scRNA-seq, snRNA-seq, ATAC-seq, and spatial transcriptomics pipelines for large-scale omics analysis.
Workflow & Infrastructure
Scalable, reproducible workflows with Nextflow, nf-core, Snakemake, Docker, and CI/CD — deployed across HPC and cloud.
Bioinformatics & Statistics
Differential expression, GSEA, pathway enrichment, gene ontology, statistical QC, and metadata harmonization.
Machine Learning
ML model benchmarking, classification, and prediction for transcriptomic and histopathology data.
HPC & Cloud
SLURM-based HPC, Linux systems, AWS (S3, EC2, Batch), and FAIR data principles for reproducible research.
Omics Tools & Databases
Scanpy, Seurat, scVI, Squidpy, BayesSpace, and key databases: GEO, NCBI, Ensembl, TCGA, ENCODE.
Work Experience
Bioinformatics Analyst
Jan 2025 – May 2025University of Texas at Dallas · Richardson, TX
- Ran RNA-seq and TWAS pipelines across ~1,100 human samples on SLURM HPC; delivered cohort results on schedule
- Debugged Nextflow failures (memory limits, malformed inputs, partial batches); reduced reruns and improved throughput
- Built Python QC tooling using matplotlib/pandas to validate outputs, flag normalization issues, and audit runs
- Communicated QC findings and pipeline outputs to research leads across multi-investigator projects
- Maintained FAIR-compliant version-controlled pipelines and documentation using Git for full reproducibility and traceability across the cohort
Microbiologist
Aug 2021 – Mar 2022Sree Vidyanikethan Degree College · Tirupathi, India
- Performed antimicrobial susceptibility assays per CLSI SOPs to characterize resistant strains and refine protocols
- Centralized lab SOPs and records to improve consistency and reproducibility across experiments
Featured Work
Deep dives into my most impactful projects — each one built to solve a real biological question.
Spatial Transcriptomics Cohort Pipeline
CRC-TME: Tumor Heterogeneity Analysis
Yeast-Stress: Automated RNA-Seq Pipeline
More Projects
Pan-Cancer Expression Profiling
DESeq2 differential expression across 5 TCGA cancer types (breast, colorectal, lung, liver, kidney). Survival analysis and prognostic biomarker identification across ~2,000 samples.
View →Gleason AI: Histology Classifier
ResNet-50 CNN for prostate cancer grading with Grad-CAM interpretability.
View →TinyVariant: Pathogenicity Benchmarking
ML benchmarking on ~100k ClinVar variants — logistic regression vs. neural net comparison.
View →SeqMorph: Mutation Simulator
CLI tool for injecting synthetic mutations to stress-test alignment algorithms.
View →CORE-seq: Sequence Compression
High-performance library for optimizing nucleotide storage for ML pre-processing.
View →Nociception Study
Molecular docking of gut microbial metabolites to host nociceptor proteins. Identified candidate metabolites with predicted binding affinity to pain receptor targets.
Education & Certifications
MS: Bioinformatics & Computational Biology
- Applied Bioinformatics
- Statistics in Bioinformatics
- Molecular Biology
- Algorithms & Data Structures
- Medical Image Analysis
Advanced Diploma: Bioinformatics
- Biological Informatics
- Biostatistics
- Data Mining & ML
- Molecular Modeling
- R & Data Analytics
BSc: Microbiology, Biochemistry, Chemistry
- Microbial Physiology
- Medical Microbiology
- Immunology
- Biomolecules
- Biotechnology
Certifications
AWS Educate: Cloud Computing 101
Foundational training on cloud computing infrastructure, services, deployment models, and best practices.
Hello Nextflow Certificate
Passed the Hello Nextflow test at the conclusion of the Nextflow training week (September 2025).
Get In Touch
Open to opportunities in bioinformatics, computational biology, and data science. I also welcome collaborations on pipeline optimization and machine learning for genomics.
Typically responds within 24 hours. Prefer a quick call? Mention it in your message.