TriTan: An efficient triple non-negative matrix factorisation method for integrative analysis of single-cell multiomics data
收藏DataCite Commons2023-12-13 更新2024-07-13 收录
下载链接：
https://figshare.manchester.ac.uk/articles/dataset/TriTan_An_efficient_triple_non-negative_matrix_factorisation_method_for_integrative_analysis_of_single-cell_multiomics_data/23283998/1
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资源简介：
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.
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提供机构：
University of Manchester
创建时间：
2023-06-05
