Fig. 3: Breast and prostate cancer analysis. | Nature Communications

Fig. 3: Breast and prostate cancer analysis.

From: Pan-cancer and cross-population genome-wide association studies dissect shared genetic backgrounds underlying carcinogenesis

Fig. 3

a Forest plot of genetic correlations between breast and prostate cancer in BBJ, UKB, and FinnGen. Dots indicate genetic correlations and whiskers represent 95% confidence intervals. b Heatmap describing the associations between the three GWAS meta-analyses of breast and prostate cancer and the top-ranking gene sets associated with the meta-analysis across breast and prostate cancer. The “Meta” column represents the meta-analysis across breast and prostate cancer. P-values of the heatmap are uncorrected and reflect two-sided tests. FDR was calculated via the Benjamini-Hochberg method across all gene sets. c Results of the cell type-specific analysis. UMAP visualizations of the breast cancer scRNA-seq dataset colored by cell type (top) and disease scores calculated via scDRS (middle). Heatmap describing the associations between the three GWAS meta-analyses of breast and prostate cancer and the cell types detected in the scRNA-seq datasets of breast and prostate cancer (down). The “Meta” column represents the meta-analysis across breast and prostate cancer. P-values of the heatmap are uncorrected and reflect two-sided tests. FDR was calculated via the Benjamini-Hochberg method across all cell types in each scRNA-seq dataset.

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