SECANT: a biology-guided semi-supervised method for clustering, classification, and annotation of single-cell multi-omics.

ABSTRACT: The recent advance of single cell sequencing (scRNA-seq) technology such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) allows researchers to quantify cell surface protein abundance and RNA expression simultaneously at single cell resolution. Although CITE-seq and other similar technologies have gained enormous popularity, novel methods for analyzing this type of single cell multi-omics data are in urgent need. A limited number of available tools utilize data-driven approach, which may undermine the biological importance of surface protein data. In this study, we developed SECANT, a biology-guided SEmi-supervised method for Clustering, classification, and ANnoTation of single-cell multi-omics. SECANT is used to analyze CITE-seq data, or jointly analyze CITE-se

SUBMITTER: Wang X 

PROVIDER: S-EPMC9491696 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature