Xiyu Peng

The paper introduces SpatialTopic, a Bayesian topic model for multiplexed imaging analysis that identifies spatial features and tracks their dynamics across disease progression.

CellGate automates spatial immunophenotyping of multiplexed tissue images with high accuracy, enabling scalable analysis of tumor-immune microenvironments.

The paper uses topic modeling to analyze T cell dynamics in cancer patients, identifying three latent topics associated with clinical outcomes and immune responses.

DAUMI improves UMI-based abundance estimation by accounting for UMI collisions and errors, outperforming existing methods on simulated and real data.

AmpliCI improves denoising of Illumina amplicon data by using a model-based approach that incorporates quality information, outperforming existing methods.