Johannes Ostner

The paper introduces cosmoDA, a differential abundance testing method for compositional sequencing data that reduces false positives by modeling feature interactions and covariates.

Pertpy provides a modular framework for analyzing large-scale perturbation single-cell experiments, offering tools for metadata annotation and perturbation distance calculations.

BacSC is a computational pipeline for bacterial single-cell RNA sequencing data that automates quality control, dimension reduction, and clustering, improving subpopulation detection across multiple bacterial species.

The paper introduces tascCODA, a Bayesian model for analyzing compositional data from amplicon and single-cell sequencing, showing improved performance in identifying compositional changes in microbial and cell type data.

scCODA is a Bayesian model for analyzing compositional single-cell data, improving detection of cell type changes in disease and other stimuli.