Automated single-cell omics end-to-end framework with data-driven batch inference.

ABSTRACT: To facilitate single-cell multi-omics analysis and improve reproducibility, we present single-cell pipeline for end-to-end data integration (SPEEDI), a fully automated end-to-end framework for batch inference, data integration, and cell-type labeling. SPEEDI introduces data-driven batch inference and transforms the often heterogeneous data matrices obtained from different samples into a uniformly annotated and integrated dataset. Without requiring user input, it automatically selects parameters and executes pre-processing, sample integration, and cell-type mapping. It can also perform downstream analyses of differential signals between treatment conditions and gene functional modules. SPEEDI's data-driven batch-inference method works with widely used integration and cell-typing tools. By d

SUBMITTER: Wang Y 

PROVIDER: S-EPMC11491117 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature