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Proteomic landscape of epithelial ovarian cancers

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zzov

ML_non-carcinoma_vs_carcinoma, zzov_ML_non-carcinoma_vs_carcinoma: These codes are used for machine learning analysis in Figure 5 and Supplementary Figure 5.

zzov_Fig1_BC This code is about generating boxplots for protein quantification of different types of samples and t-SNE plots for the samples in Figure 1B&C.

zzov_Fig1_BC_sfig1B,C,D,E,F,G This code is about performing t-SNE analysis on pooled samples and analyzing the correlation between technical replicates and biological replicates in sFigure 1B&C&D&E&F&G.

zzov_boxplot_fig3, zzov_boxplot_fig3C These code are used to visualize the boxplot in Figure 3.

zzov_heatmap_fig6E, zzov_heatmap_fig7A These code are used to visualize the heatmap analysis in Figure 6E.

zzov_heatmap_sankey_fig3 This code is about generating heatmap analysis and Sankey analysis plots in Figure 3A.

zzov_plasma_ml_fig5 This code is about analyzing SHAP values of machine learning results and conducting survival analysis in Figure 5.

zzov_qc_pca_cv This code is the quality control for proteomics of plasma samples in SFigure 3A&B&D.

zzov_t-test_FTE_vs_OSE This code is about performing differential analysis between FTE samples and OSE samples.

zzov_tissue_ml_fig5 This code is about machine learning analysis using the XGBoost method and survival analysis on tissue samples in Figure 5.

zzov_volcano_fig6B The volcano plot showed comparison of proteome between chemosensitive HGSOC patients with HRR mutations and chemoresistant ones without any HRR mutations in Figure 6B.

zzov_volcano_sfig4B This code is about generating volcano plots for differential analysis between different groups of samples in SFigure 4B.

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