Extended Data Fig. 8: Single-cell embeddings and transcriptome comparisons of scifi-RNA-seq and droplet-based scRNA-seq.

An equal mixture of four human cell lines (HEK293T, Jurkat, K562, NALM-6) was processed in parallel with scifi-RNA-seq and with the Chromium 3’ v3.1 Single Cell Gene Expression kit. a, Single-cell transcriptomes displayed in a two-dimensional UMAP projection, with cluster IDs identified by the Leiden algorithm mapped on top. Enrichment of cell line signatures obtained from the ARCHS4 database for the identified Leiden clusters. These results can be used to assign the respective cell line for each cluster, and to identify spurious clusters of doublet cells. b, Joint embeddings combining data across methods (scifi-RNA-seq, standard droplet-based scRNA-seq) and sample preparation methods (intact cells, nuclei, methanol-fixed cells), using dimensionality reduction by principal component analysis (PCA), uniform manifold approximation and projection (UMAP), diffusion maps, t-distributed stochastic neighbor embedding (t-SNE), and the ForceAtlas2 algorithm. Individual cells are colored by cell line (top panel) or sample preparation method (bottom panel). The grouping by cell line (rather than by assay or sample preparation method) was observed without batch effect correction. c, The separation of cells in the latent spaces was quantified using the silhouette score. d, Overlap in the top-100 differential genes between cell lines. e, Correlation matrices of log fold changes, p-values, and test statistics across assays and sample preparation methods.