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Fig. 2 | Biology Direct

Fig. 2

From: Large-scale bulk and single-cell RNA sequencing combined with machine learning reveals glioblastoma-associated neutrophil heterogeneity and establishes a VEGFA+ neutrophil prognostic model

Fig. 2

Developmental Trajectory Characteristics of GBMAN. (A) Diffusion map visualization of the distribution of four neutrophil subsets. The diffusion map captures the underlying structure of the data, revealing the relative positions and relationships of the four neutrophil subsets. (B-D) Feature plots respectively display the pseudotime, differentiation potential, and stemness score. (E) Boxplot shows a comparison of N2 scores among the four subgroups. (F) Gene trajectories were clustered based on expression patterns over pseudotime, and functional enrichment analyses were performed for Gene Ontology Biological Processes (GO_BP), Molecular Functions (GO_MF), Cellular Components (GO_CC), and KEGG pathways. (G) Scatterplot depicting the correlation between pseudotime (developmental progression) and differentiation potential for each neutrophil subset. The plot reveals how the differentiation potential changes as cells progress along the pseudotime trajectory. (H) Scatterplots showing the association between pseudotime and key functional states, including hypoxia, glycolysis, interferon-γ response, and immune response. These plots illustrate how cellular functional states evolve along the developmental continuum

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Biology Direct

ISSN: 1745-6150

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