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Fig. 3 | BMC Bioinformatics

Fig. 3

From: Detection of cell markers from single cell RNA-seq with sc2marker

Fig. 3

Ranking of markers and computational time for all the evaluated methods: Distribution of the ranks of true markers for the MCA-Spleen (A), MCA-Lung (B), Human-Lung &PBMC (C), Human-BM (bone marrow CITE-seq data) (D), and Human-PBMC (human peripheral blood mononuclear cells CITE-seq data) (E) data sets for all evaluated methods. For simplicity, the distributions and ranks of all the cell types were combined for a given method and data set. The methods that gave lower ranks for the true markers were the best in recovering the true cell markers. (F) Distribution of computational time for all the evaluated methods in seconds. Methods are ranked by increasing median value and values are shown in log 10 scale. The statistical significance of the best overall method (sc2marker + DB) compared with the other computing method is indicated as; * p-value < 0.1, ** p-value < 0.01, *** p-value < 0.001, **** p-value < 0.0001 by the Wilcoxon rank sum test (adjusted using the Bonferroni correction)

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