![]() We chose 10 here, but encourage users to consider the following: In this example, all three approaches yielded similar results, but we might have been justified in choosing anything between PC 7-12 as a cutoff. The third is a heuristic that is commonly used, and can be calculated instantly. The second implements a statistical test based on a random null model, but is time-consuming for large datasets, and may not return a clear PC cutoff. The first is more supervised, exploring PCs to determine relevant sources of heterogeneity, and could be used in conjunction with GSEA for example. We therefore suggest these three approaches to consider. Identifying the true dimensionality of a dataset – can be challenging/uncertain for the user. Interoperability between single-cell object formats.Demultiplexing with hashtag oligos (HTOs). ![]() Integrating scRNA-seq and scATAC-seq data.Fast integration using reciprocal PCA (RPCA).Analysis, visualization, and integration of spatial datasets with Seurat. ![]()
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