SYSTEMS, SOFTWARE, AND METHODS FOR MULTIOMIC SINGLE CELL CLASSIFICATION AND PREDICTION AND LONGITUDINAL TRAJECTORY ANALYSIS

A system analyzes and maps the immune system through observational genomics, using multiomic single-cell technologies and machine learning, and uses functional genomics for therapy development including treatment outcome analysis, prediction, and recommendations based on multiomics and longitudinal trajectory analysis. Annotation is performed based on a multiomic classifier and the annotation is validated using RNA/protein pattern recognition per cell subset. Annotating may include automated cell type prediction including dimensionality reduction, feature extraction & automated cell type prediction, multiomic batch effect correction and multiomic based multiplet removal, and may involve separation of sub-cell types. Multiomic data used may comprise gene expression data, CITE seq markers, and TCR/BCR data. Cell type specific matching of clinical signatures with perturbation signatures may include mapping signature against large scale CRISPR perturbations in relevant cell type to identify potential drug targets. Mapping may include signature mapping to clinical covariate.