Jana M. Braunger

msBayesImpute improves missing value handling in proteomics data by integrating Bayesian factorization and probabilistic dropout models, outperforming existing methods in imputation and normalization.

The paper maps variant, enhancer, and gene function in primary human CD4+ T cells by combining Perturb-seq of regulatory elements and genes, identifying CRE-gene pairs and linking variants to disease-related programs.

The paper presents a genome-scale CRISPRi perturbation map in human pluripotent stem cells using single-cell RNA sequencing to study trans gene regulation across diverse genetic backgrounds.

The paper introduces crispat, a tool for guide assignment in single-cell CRISPR screens, showing differences in results across strategies.

MEFISTO enables spatio-temporal dimensionality reduction and pattern separation in multi-modal genomic data, revealing conserved and diverged developmental programs and microbiome heterogeneity.

decoupleR evaluates methods for inferring biological activities from omics data, finding simple linear models and consensus scores perform best in perturbation experiments.