Chiung-Ting Wu

swCAM estimates subtype-specific expressions in individual samples using unsupervised deconvolution, revealing changes in cell proportions and gene expression in bipolar disorder.

This paper introduces an unsupervised deconvolution method, CAM3.0, to determine molecular archetype composition and expression from bulk tissues, showing its effectiveness through simulations and case studies.

This paper introduces OVE-FC and OVE-sFC tests to detect subtype-specific and differentially expressed genes, showing improved accuracy in deconvolution compared to existing methods.

COT detects marker genes across subtypes using cosine similarity in a one-sample test, applicable to multi-omics data.

The paper uses cell-type deconvolution to analyze gene expression in schizophrenia and finds upper-layer neurons in the DLPFC are associated with SCZ risk.

This paper introduces ncGTW, a method to align LC-MS profiles by detecting and correcting misalignments using compound-specific warping functions and neighbor constraints.

SynQuant quantifies synapses from microscopy images by addressing antibody specificity, brightness heterogeneity, and noise, showing improved performance over existing tools in disease models.

This paper proposes two computational methods to integrate multi-omics data and identify disease-specific pathways, demonstrating their effectiveness on muscular dystrophy data.