Network-based logistic regression integration method for biomarker identification.

ABSTRACT:

Background

Many mathematical and statistical models and algorithms have been proposed to do biomarker identification in recent years. However, the biomarkers inferred from different datasets suffer a lack of reproducibilities due to the heterogeneity of the data generated from different platforms or laboratories. This motivates us to develop robust biomarker identification methods by integrating multiple datasets.

Methods

In this paper, we developed an integrative method for classification based on logistic regression. Different constant terms are set in the logistic regression model to measure the heterogeneity of the samples. By minimizing the differences of the constant terms within the same dataset, both the homogeneity within the same dataset and the heterogeneity in mu

SUBMITTER: Zhang K 

PROVIDER: S-EPMC6311907 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature