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 8. Animal experiment validation in epididymis (NOA: irradiation-induced non-obstructive azoospermia mice, Control: control group): Relative mRNA expression of signature genes (C12orf54, TSSK6, OR2H1, FER1L5, C9orf153) in epididymis. (^*indicates P < 0.05, ^**indicates P < 0.01, ^***indicates P < 0.001).