Identification and validation of diagnostic signature genes in non-obstructive azoospermia by machine learning

Lingxiang Ran; Zhixiang Gao; Qiu Chen; Fengmei Cui; Xiaolong Liu; Boxin Xue

doi:doi:10.18632/aging.204749

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Research Paper Volume 15, Issue 10 pp 4465—4480

Identification and validation of diagnostic signature genes in non-obstructive azoospermia by machine learning

Figure 2. Differentially expressed genes in NOA versus control. (A) PCA plot of training datasets. (B) Volcano plot for the DEGs. (C) Heatmap for the DEGs. (D) KEGG analysis of upregulated pathways. (E) KEGG analysis of downregulated pathways. (F) GSEA analysis of upregulated pathways. (G) GSEA analysis of downregulated pathways. (P < 0.05, Abbreviations: NOA: non-obstructive azoospermia; CON: control group).