Cong Ma

CalicoST infers allele-specific copy number aberrations and tumor phylogeography from spatially resolved transcriptomics data, achieving higher accuracy than existing methods.

Belayer models both continuous and discrete spatial variation in gene expression from spatially resolved transcriptomics data, accurately identifying tissue layers and spatially varying genes.

The paper introduces a computational method to detect transcriptomic structural variants in heterogeneous samples by solving the Multiple Compatible Arrangements Problem, showing improved performance over existing tools.

This paper introduces a corrected estimator for mutual information that accounts for measurement error, showing improved accuracy in simulated and real gene expression data.