Identification of SIK1 as a signature gene in asthma by machine learning. (IMAGE)

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Identification of SIK1 as a signature gene in asthma by machine learning.

Caption

(A, B) LASSO regression identified 22 key genes associated with asthma. (C) The SVM-RFE algorithm identified a total of 26 key genes associated with asthma. (D) The intersection of LASSO and SVM-RFE methods revealed a set of 11 key genes associated with asthma. (E, F) Using Random Forest and XGBoost to rank the importance of 11 key genes. (G–I) The expression level of SIK1 in the GSE152004, GSE143303, and GSE65204 datasets of asthma. LASSO, least absolute shrinkage and selection operator; SVM-RFE, support vector machine-recursive feature elimination; XGBoost, extreme gradient boosting.

Credit

Juntong Liu, Yue Wang, Lingyun Zou, Xinyue Han, Mingqi Lv, Xichuan Deng, Jingjing Liao, Guangchao Zang, Lei Xu, Tianle Gu, Nan Lu, Guangyuan Zhang

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