Junior Research Collaborator | Computational Biologist | Bioinformatics Analyst
Building reproducible pipelines and interactive dashboards for infectious disease genomics and AMR surveillance
flowchart LR
A[Biological Question\nAMR · Genomics · Epidemiology] --> B[Data Collection\nGEO · SRA · TyphiNET · NCBI]
B --> C[Reproducible Pipeline\nR · Bash · DESeq2 · HISAT2]
C --> D[Statistical Analysis\nDEG · AMR Trend · Variant Surveillance]
D --> E[Interactive Visualization\nShiny Dashboard · Quarto Report]
E --> F[Communication\nGitHub Pages · LinkedIn · Documentation]
I work at the intersection of infectious disease biology and computational data analysis — turning messy genomic and epidemiological datasets into reproducible, interactive tools that researchers can actually use.
Languages & Frameworks
Bioinformatics & Genomics
Visualization & Dashboards
Tools & Reproducibility
A 24-year retrospective analysis of Salmonella Typhi antimicrobial resistance trends in Bangladesh, extending Tanmoy et al. 2024 (PLOS NTDs) with TyphiNET genomic data. Fully deployed as an interactive Shiny dashboard and a Quarto report on GitHub Pages.
Highlights:
- Integrated clinical AMR phenotype data with whole-genome sequencing genotype data from TyphiNET
- Visualized multi-drug resistance (MDR), XDR, and H58 lineage trends over 24 years
- Deployed interactive Shiny dashboard with tabbed navigation and downloadable outputs
- Published reproducible Quarto report with embedded figures and methodology
Tech: R Shiny ggplot2 Quarto renv GitHub Pages TyphiNET AMR genomics
🔗 View Repository · 📊 Live Dashboard · 📄 Quarto Report
Reproduced bulk RNA-Seq analysis from a high-impact immunology paper on IL-10 receptor-deficient microglia. Discovered that the GEO deposit contains UTAP-normalized counts (not raw counts) — a methodological finding documented publicly and shared with the research community, attracting engagement from scientists at Illumina, Novartis, Pfizer, and GSK.
Highlights:
- Replicated differential expression analysis using DESeq2 with apeglm shrinkage
- Identified 1,563 DEGs with clean mutant/control separation
- Documented GEO data transparency issue publicly, reaching 6,300+ LinkedIn impressions
- V2 pipeline in progress from raw FASTQs via SRA for full methodological rigor
Tech: R DESeq2 apeglm ggplot2 pheatmap Shiny GEO SRA Bioconductor
🔗 View Repository · 📊 Live Dashboard
Interactive R Shiny dashboard analyzing DENV-2 sequences from the 2023 Bangladesh dengue outbreak (Dhaka & Chattogram isolates). Includes QC filtering, motif detection, and comparative visualization.
Highlights:
- Analyzed 13 real DENV-2 sequences from the 2023 Bangladesh outbreak
- Detected conserved motifs and visualized variant patterns across isolates
- Deployed interactive dashboard with modern tabbed UI
Tech: R Shiny Bioconductor sequence analysis genomic surveillance
🔗 View Repository · 📊 Live Dashboard
Exploratory analysis of 1,025 clinical patient records to identify risk factors for heart disease. Combined Python + SQL workflow with a six-panel diagnostic visualization dashboard.
Highlights:
- 8 standalone SQL queries on SQLite for structured data retrieval
- Identified maximum heart rate as the strongest predictor; challenged cholesterol assumptions
- Fully documented, reproducible Jupyter Notebook with biological interpretation
Tech: Python SQL SQLite Pandas Matplotlib Seaborn Jupyter
- Infectious Disease Genomics & AMR Surveillance
- RNA-Seq & Multi-omics Data Analysis
- Reproducible Bioinformatics Tools & Workflows
- Public Health Data Science
- Computational Biology & Interactive Dashboards
- Email: faiyaj.mdabrar@gmail.com
- ORCID: 0009-0005-9646-4508
- LinkedIn: md-abrar-faiyaj
Open to research collaborations, bioinformatics roles, and PhD opportunities in computational biology and infectious disease genomics.
Last updated: June 2026