Rong Ma

FlowMap jointly models cellular states and dynamics in a geometric framework, recovering interpretable trajectories and developmental patterns from single-cell RNA sequencing data.

The paper introduces SEEK-VFI, a method for selecting trajectory-relevant genes in single-cell analysis, which improves trajectory inference and downstream analyses.

SEEK-VEC improves topic modeling by combining multiple models through spectral ensembling, enhancing performance in identifying vocabulary and relationships, especially with weak signals.

MOSAIC integrates single-cell multi-omics data to identify feature connectivity patterns, revealing biological rewiring and improving clinical outcome prediction.

This study investigates synaptic connectivity development in the mouse cerebellum, revealing sequential input-dependent wiring and individualized parallel fiber inputs to Purkinje cells.

The paper introduces NESS, a method to improve neighbor embeddings in single-cell data by leveraging stability, enabling better inference of smooth biological structures and cell-state transitions.

The paper introduces a method to identify spatially variable genes by projecting spatial transcriptomics data onto morphologically relevant curves, improving detection accuracy and biological interpretation.

SPRITE improves spatial gene expression predictions by integrating gene networks and spatial relationships, enhancing clustering and classification in spatial transcriptomics data.

TISSUE improves spatial transcriptomics analysis by providing uncertainty-calibrated predictions, enhancing downstream tasks like clustering and differential expression analysis.

This study introduces hybrid BAG-seq to analyze DNA and RNA from single nuclei in tumor samples, revealing genome-transcriptome interactions and tumor heterogeneity.

This paper introduces SMAI, a framework for alignability testing and integration of single-cell data, showing it outperforms existing methods and improves downstream analyses.

This study maps expression and splicing QTLs in East Africans and finds population-specific genetic variation related to immunity, metabolism, and pigmentation.

The paper introduces a spectral method to evaluate and combine multiple data visualizations, improving the quality of the consensus visualization by leveraging eigenscores.

DynamicViz generates dynamic visualizations to assess the reliability of dimensionality reduction methods by quantifying dynamic variability in data.