ScDeepInsight: a supervised cell-type identification method for scRNA-seq data with deep learning.

ABSTRACT: Annotation of cell-types is a critical step in the analysis of single-cell RNA sequencing (scRNA-seq) data that allows the study of heterogeneity across multiple cell populations. Currently, this is most commonly done using unsupervised clustering algorithms, which project single-cell expression data into a lower dimensional space and then cluster cells based on their distances from each other. However, as these methods do not use reference datasets, they can only achieve a rough classification of cell-types, and it is difficult to improve the recognition accuracy further. To effectively solve this issue, we propose a novel supervised annotation method, scDeepInsight. The scDeepInsight method is capable of performing manifold assignments. It is competent in executing data integration throu

SUBMITTER: Jia S 

PROVIDER: S-EPMC10516353 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature