Methylation marker and application thereof in diagnosis and classification of tumors
A methylation marker and methylation technology, applied in the field of biomedicine, can solve problems such as the application of unproven markers
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Embodiment 1
[0076] For the diagnostic methylation markers, the samples of 12 kinds of tumors (paired tumor tissue and normal tissue) in TCGA were first used for feature selection, and the specific steps were as follows:
[0077] (1) Use XGBoost for training. The parameter is to use the GridSearchCV function in sklearn to perform 5-fold cross-validation automatic parameter adjustment. After training, the importance score of each feature (the methylation level of the probe (CpG island)) is obtained. Delete The feature corresponding to the minimum score.
[0078] (2) Repeat step (1) for the data composed of the remaining features until there is only one feature left.
[0079] (3) Too many features lead to high cost of clinical detection, and too few features lead to a decrease in prediction accuracy. Considering this comprehensively, the top 7 CpG islands in the feature importance score were selected as markers for tumor diagnosis.
[0080] (4) Using the methylation levels of the above 7 CpG ...
Embodiment 2
[0086] For the classifier to distinguish different tumors, the tumor samples of TCGA tumors are firstly analyzed according to the following steps:
[0087] In this embodiment, the tumor samples may also come from other data sets.
[0088] In this embodiment, the tumor can also be selected according to actual needs.
[0089] (1) The methyl chip data of tumor patients with 26 kinds of cancers were combined together, including 7605 patient samples; among them, the relevant information of 26 kinds of cancers is shown in Table 3.
[0090] (2) Variance screening: delete probes whose variance (std) in all samples is less than 0.2.
[0091] (3) Differential methylation screening: in each cancer, the top 20 probes that were differentially methylated between this cancer and the remaining 25 cancers (average difference >0.3 & FDR <0.01) were selected. A total of 515 CpG islands were screened out and reserved for further screening. These 515 CpG islands can well distinguish different t...
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Abstract
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