TriTan: An efficient triple non-negative matrix factorisation method for integrative analysis of single-cell multiomics datarevision.zip contains tutorial and benchmark datasets

<ul> <li>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. </li> <li>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.</li> <li>Bone marrow mononuclear cells (NeurIPS 2021 ) of 10X Multiome from GSE194122. GSE194122.zip contains prepocessed .h5mu data as well as ground truth.</li> <li>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.</li> </ul> <p><br></p>