Fig. 1: Neomers can detect cancer tissue of origin.
From: Leveraging sequences missing from the human genome to diagnose cancer
a Schematic overview of neomer cancer diagnostic pipeline. Created in Biorender. Ahituv, N. (2025) https://BioRender.com/9sgstbs. b–f 2577 patients across 21 cancer types were used. b Number of neomers per patient sample across tissues. Each dot represents a patient sample. The boxplot displays the median as the central line. The bottom and top edges of the box represent the first quartile (25th percentile) and third quartile (75th percentile), respectively. The lower and upper whiskers extend to the smallest and largest data values that fall within 1.5 times the interquartile range above the 25th percentile and below the 75th percentile. c Number of neomers and the number of substitutions for 2577 patients (Spearman’s ρ = 0.75). d Identification of nullomers at driver mutation sites across cancer tissues. The majority of cancer driver mutations result in the resurfacing of nullomers. The proportion of mutations that cause the resurfacing of nullomers is indicated under each cancer type. e Heatmap showing the Jaccard index for the overlap of neomer sets associated with different cancer types. f Heatmap showing the occurrence of neomers across patients for each cancer type. Each row represents a cancer type and each column a patient. The intensity of the heatmap (log2-scale) shows the number of neomers for each tissue set.
