Fig. 7: Differential gene ontology (GO) profiles comparing True versus False classifications within the PathoRiCH-predicted favorable and poor outcome groups. | Nature Communications

Fig. 7: Differential gene ontology (GO) profiles comparing True versus False classifications within the PathoRiCH-predicted favorable and poor outcome groups.

From: Histopathologic image–based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer

Fig. 7

a Within the favorable outcome predictions, the true favorable-predicted (n = 134) predominantly featured genes involved in immune response, and the false favorable-predicted (n = 25) category was enriched for ribosomal- and mitochondrial-associated genes. b Within the poor outcome predictions, the true poor-predicted (n = 19) group was characterized by genes associated with the extracellular matrix, and the false poor-predicted (n = 30) category was enriched for mitochondrial- and ribosomal-associated genes. ClusterProfiler58 was used for both GO analysis with a Benjamini–Hochberg procedure.

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