Jana Biermann

Processing-bias correction with DEBIAS-M improves cross-study generalization of microbiome-based prediction models

DEBIAS-M corrects processing bias in microbiome data, improving cross-study generalization of prediction models by learning interpretable bias-correction factors.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

This study creates a single-nucleus and spatial transcriptomic atlas of the COVID-19 liver, revealing cellular and functional disruptions associated with organ damage.

Echidna: A Bayesian framework for quantifying gene dosage effect impacting phenotypic plasticity

Echidna quantifies gene dosage effects on phenotypic plasticity by integrating scRNA-seq and WGS data to separate genetic from cell non-autonomous mechanisms.

KINOMO: A non-negative matrix factorization framework for recovering intra- and inter-tumoral heterogeneity from single-cell RNA-seq data

KINOMO improves the analysis of single-cell RNA-seq data by recovering intra- and inter-tumoral heterogeneity through non-negative matrix factorization, outperforming existing methods in benchmarking.

Multi-modal single-cell and whole-genome sequencing of minute, frozen specimens to propel clinical applications

This study develops a method for single-cell and whole-genome sequencing of frozen clinical specimens, demonstrating its utility in analyzing tumor evolution and rare disease biospecimens.