C-COMPASS: a user-friendly neural network tool profiles cell compartments at protein and lipid levels.

ABSTRACT: Systematic proteomic organelle profiling methods including protein correlation profiling and LOPIT have advanced our understanding of cellular compartmentalization. To manage the complexity of organelle profiling data, we introduce C-COMPASS, a user-friendly open-source software that employs a neural network-based regression model to predict the spatial cellular distribution of proteins. C-COMPASS handles complex multilocalization patterns and integrates protein abundance to model organelle composition changes across conditions. We apply C-COMPASS to mice with humanized livers to elucidate organelle remodeling during metabolic perturbations. Additionally, by training neural networks with co-generated marker protein profiles, C-COMPASS extends spatial profiling to lipids, overcoming the lac

SUBMITTER: Haas DT 

PROVIDER: S-EPMC12791020 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature