Welcome!
I'm John Caperella, a bioinformatics specialist with an M.S. from Brandeis University and a background in biochemistry.
This hub features interactive tools I’ve built for RNA-Seq, ATAC-Seq, miRNA-Seq, and DNA methylation analysis—each one designed to simplify complex workflows and support life science research with minimal coding required.
These apps aren’t just dashboards—they’re full-stack, no-nonsense tools built to handle every major task for each data type. From QC to differential expression to visualization, they do everything your little heart could desire.
RNA-Seq Analysis App
A fully interactive Shiny app for bulk RNA-Seq analysis. Upload your counts CSV file to run differential expression via Limma/vroom, explore QC plots (PCA, heatmaps, boxplots), and export both raw results and publication-ready images.
Designed for ease-of-use, but powerful enough for serious bioinformatics workflows.
ATAC-Seq Analysis App
This app streamlines ATAC-Seq analysis for non-programmers. Includes quality control, differential peak detection, and downstream visualization—all within an intuitive, point-and-click Shiny interface.
View on GitHubmiRNA-Seq Shiny App
A user-friendly app for miRNA-Seq differential expression analysis and visualization. Designed to help biologists run complex analyses without needing to touch code.
View on GitHubDNA Methylation Analysis App
A fully interactive Shiny app for analyzing DNA methylation data from arrays such as Illumina 450k. Features include differential methylation analysis (DE), pathway enrichment using Enrichr, PCA/UMAP visualizations, Random Forest classification, and power analysis. Optimized for both local and HPC environments via Singularity/Apptainer.
View on GitHub