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Fig. 2 | Genome Biology

Fig. 2

From: MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions

Fig. 2

Evaluation of within-MC transcriptional homogeneity. a Shown are the number of incoming and outgoing neighbors (or degree) per cell, averaged over metacells that are color-coded by cell type annotation as in Fig. 1. The data represent the raw K-nn similarity graph (left), balanced MC graph (center), and resampled co-occurrence graph (right). b Heat map summarizing the number of edges in the balanced MC graph that link two cells associated with different MCs. Similar matrices generated based on the raw and co-occurrence graphs are shown in Additional file 2: Figure S4. c Bar graph shows the closure per MC (fraction of intra-MC edges out of all edges linking cells in the MC). d Observed (blue) vs predicted (red, based on binomial model) distributions of down-sampled UMI count per gene within MCs. For each of the 5 MCs depicted, the plots show binomial fit for the top 8 enriched genes. Intervals give 10th and 90th percentiles over multiple down-samples of the cells within each metacell to uniform total counts. e Over-dispersion of genes relative to a binomial model across genes and MCs. Colors encode ratio of observed to expected variance across genes (rows) and MCs (columns). Only genes and MCs manifesting high over-dispersion are shown. f Residual within-MC correlation patterns compared with global correlation patterns. Within-MC correlation matrix (left) was computed by averaging gene-gene correlation matrices across MCs, where each matrix was computed using log-transformed UMIs over down-sampled cells. Global correlation matrix (right) was computed in the same manner, but following permutation of the MC assignment labels. For both matrices, only genes manifesting strong correlations are shown. g Examples of residual intra-MC correlated genes, showing observed correlations (Pearson on log-transformed down-sampled UMIs) compared to correlations expected by sampling from a multinomial. MC #66 show weak residual correlations reflecting mostly stress genes. MC #70 shows stronger residual correlations, reflecting residual intra-MC variation

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