TriTan: An efficient triple non-negative matrix factorisation method for integrative analysis of single-cell multiomics data

Name: TriTan: An efficient triple non-negative matrix factorisation method for integrative analysis of single-cell multiomics data
Published: 2023-06-05T13:28:33+00:00
License: https://creativecommons.org/licenses/by/4.0/
Keywords: Single cell multi-omics

Version 2 2023-12-13, 10:22

Version 1 2023-06-05, 13:28

dataset

posted on 2023-06-05, 13:28 authored by Xin MaXin Ma

Three multiple publicly available single-cell multi-modal (two modalities - RNA and ATAC) datasets of varying sizes to comprehensively benchmark TriTan against other methods and leverage the output from TriTan for extensive downstream analyses.
PBMC-10K: Human peripheral blood mononuclear cells of 10X Multiome from(https://www.10xgenomics.com/resources/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) . pbmc10k.h5mu : .h5mu data with two modalities; PBMC-10K-celltype.txt: ground truth cell type labels.
Bone marrow mononuclear cells (NeurIPS 2021 ) of 10X Multiome from GSE194122. GSE194122.zip contains prepocessed .h5mu data as well as ground truth.
Mouse skin cells using SHARE-seq protocol from GSM4156597. The .zip data contains prepocessed and unprepossed scRNA-seq and scATAC-seq data.; GSM4156597_skin_celltype.txt:ground truth cell type labels.