tinydenseR is a landmark-based platform for single cell data analysis that identifies differentially abundant cell types and differentially expressed features, including subtle within-cluster state changes. Modeling samples as replicates, tinydenseR enhances analytic efficiency and reproducibility while preserving the richness of single cell data

singeCellComic is an interactive Shiny application designed to teach the fundamental concepts of single-cell RNA sequencing (scRNA-seq) analysis through a fun, story-driven, and visual narrative.

A Python library for benchmarking uncertainty estimation and quantification methods for Machine Learning models predictions.

Deep survival analysis made easy

Cellxgene Gateway allows you to use the Cellxgene Server provided by the Chan Zuckerberg Institute (https://github.com/chanzuckerberg/cellxgene) with multiple datasets.

Bayesian subgroup shrinkage estimation benchmark comparing various shrinkage models.

This pipeline is designed for AAV integration site analysis using Target Enrichment Sequencing (TES) coupled with PacBio long-read sequencing. It enables the detection of integration site breakpoints and provides information on the structure of the integrated AAV vector genome to support the safety assessment of AAV-based gene therapies.

Parse a simplified JSONPath-like syntax

Applied modelling in drug development: flexible Bayesian regression modelling in Stan via brms

The codebase created to support the application of artificial intelligence for predicting the subcellular localization of solute carrier transporter (SLC) proteins. We developed an iterative method that harmonizes human annotations with AI-based model outputs.