GSTRPCA: irregular tensor singular value decomposition for single-cell multi-omics data clustering.

ABSTRACT: Single-cell multi-omics refers to the various types of biological data at the single-cell level. These data have enabled insight and resolution to cellular phenotypes, biological processes, and developmental stages. Current advances hold high potential for breakthroughs by integrating multiple different omics layers. However, singlecell multi-omics data usually have different feature dimensions and direct or indirect relationships. How to keep the data structure of these different data and extract hidden relationships is a major challenge for omics data integration, and effective integration models are urgently needed. In this paper, we propose an irregular tensor decomposition model (GSTRPCA) based on tensor robust principal component analysis (TRPCA). We developed a weighted threshold mo

SUBMITTER: Cui L 

PROVIDER: S-EPMC11647523 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature