A relay velocity model infers cell-dependent RNA velocity
All scRNA-seq data in this study were downloaded publicly .
For the pancreatic endocrinogenesis data, we followed the method by Bergen et al. in the scVelo studyFor the mouse hippocampal dentate gyrus neurogenesis data, we followed the gene and cell filtering methods by La Manno et al.For the erythroid lineage of the mouse gastrulation data, we selected 12,329 cells from cell types, including hematoendothelial progenitors, blood progenitors 1/2 and erythroid 1/2/3 in stages of E7.0, E7.25, E7.5, E7.75, E8.0, E8.25 and E8.5.
For the human embryo glutamatergic neurogenesis dataset, we kept cells with at least 200 genes expressed and kept genes that were captured in at least three cells. We identified all the high variable genes with the default settings of scanpy.pp.highly_variable_genes by using SCANPY . In total, 1,054 cells with 1,720 genes were selected. We used 200 nearest neighbors for the calculation of the first moment to reduce the noise in transcripts.
For the cell cycle progression in the REP1-FUCCI cells, we used the scEU-seq data, in which we took 3,058 cells with the top 2,000 high variable genes from the pulse experiment. The unspliced mRNA reads were calculated as the addition of the unspliced labeled and unspliced unlabeled reads, likewise for the spliced mRNA reads. We used 300 nearest neighbors for the calculation of the first moment to reduce the noise in transcripts.
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