Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Zhaoyang Guo; Yuanye Ma; Yaqing Wang; Hongfei Xiang; Huifei Cui; Zuoran Fan; Youfu Zhu; Dongming Xing; Bohua Chen; Hao Tao; Zhu Guo; Xiaolin Wu

doi:doi:10.18632/aging.204714

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Research Paper Volume 15, Issue 9 pp 3807—3825

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Figure 12. Correlation analysis of diagnostic feature biomarkers and immune infiltration cells. The lollipop diagram illustrates the correlation of 23 immune cells and (A) AKR1C3, (B) MCEE, (C) PFKM, and (D) POLE4. The dot represents the absolute value of the correlation coefficient, and the p -values are annotated with different colors. p < 0.05 is considered statistically significant.