Fig. 1: Histologically defined group-based analysis.

a–c SPATA’s manual annotation tool is employed to delineate borders, facilitating the grouping of spots based on histology. d Gene expression-driven UMAP projection of spots. e A dot plot showcases the 18 most statistically significant unique marker genes, ranked by their average log2-fold change, in accordance with histological areas. f and g Surface plots are color-coded to highlight inferred copy number alterations that are characteristic of glioblastoma. h and i Statistical analyses examine copy number alterations across histological areas (two-sided test, no adjustments for multiple comparisons, Tumor (n = 1307), Transition (n = 478), Infiltrated Cortex (n = 1428). The minima represent the smallest and the maxima represent the largest value within 1.5 times the interquartile range (IQR) below or above the first or third quartile (Q1, Q3), respectively. The median is shown as a line inside the box. The box bounds are the first quartile (Q1, 25th percentile) and the third quartile (Q3, 75th percentile). The whiskers extend from Q1 and Q3 to the minima and maxima. j A heatmap provides a comprehensive view of alterations across all chromosomes in relation to histological areas, corroborating the tumor area’s classification with multiple alterations, the nearly unaltered cortex infiltrated by the tumor, and the transition zone exhibiting intermediate levels of alterations. k A volcano plot from the DEA analysis across histological areas highlights marker genes for the Tumor and Transition areas, characterized by an adjusted p-value of 0 (infinite −log10).