Samples were from 30 patients with iCCA, 17 samples with PSC, and 20 patients with other liver diseases but not iCCA or PSC seen at Mayo Clinic, Rochester, MN between January 2000 and May 2010. Peripheral blood was collected from each participant at the time of the office visit before treatment. Sera were stored at −80°C.
To alleviate the bias of feature selection, we applied various methods such as stepwise logistic regression, Lasso algorithm, correlation filter, random forest algorithm for feature selection to optimize the combination of glycans, and cross-validations [leave-one-out cross-validation and 3-fold CV] were further applied during feature selection to avoid bias .
Cluster analysis was also applied to explore the similarity of the data structure of the glycans of interest based on statistical distances. Tanglegram of serum and TMA were plotted to explore the congruence of the two dendrograms . Principal component analysis was used for further exploring glycan data structure based on its variation-covariance , biplots of selected glycans of serum and TMA are provided for visual inspection in relationship of principal components.
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