Proteomics Meets Single-Cell: Integration and Analysis Progress
Date:
Progress report on integrating single-cell proteomics with transcriptomics for comprehensive cellular profiling. Presented advances in CITE-seq data analysis, surface protein marker identification, and joint embedding of protein and RNA measurements. Discussed computational methods for handling the unique characteristics of protein data including sparsity, dynamic range, and antibody-specific noise. Demonstrated applications in immune cell profiling, cancer heterogeneity analysis, and identifying protein-level dysregulation not captured by transcriptomics. Covered emerging technologies like spatial proteomics and multi-parameter flow cytometry analysis using deep learning.