Application of RGS19 in construction of lung squamous cell carcinoma prognosis prediction model as diagnostic marker
A diagnostic marker, RGS19 technology, applied in the field of biomedicine
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[0024] Example 1 Model construction and effect verification
[0025] 1. Method
[0026] 1.1 The training set comes from the RNA sequencing data and clinical data of 326 cases of lung squamous cell carcinoma from the TCGA database, and the expression profiles of autophagy-related genes (ARGs) are obtained. The validation set comes from the RNA sequencing data of 78 cases of lung squamous cell carcinoma from the GTO database. , to obtain all RNA expression profiles and autophagy-related gene (Autophagy-Related-Genes, ARGs) expression profiles.
[0027] 1.2 ARGs related to prognosis were screened out by survival analysis, and then the most critical survival-related ARGs (RGS19) were obtained by random forest method, and a risk prediction model based on this gene was constructed by deep machine learning method of random forest. The patients were divided into low-risk group and high-risk group according to the risk level obtained by the model. The model was validated by receiver ...
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