Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances.

ABSTRACT: Biomarker detection is one of the more important biomedical questions for high-throughput 'omics' researchers, and almost all existing biomarker detection algorithms generate one biomarker subset with the optimized performance measurement for a given dataset. However, a recent study demonstrated the existence of multiple biomarker subsets with similarly effective or even identical classification performances. This protocol presents a simple and straightforward methodology for detecting biomarker subsets with binary classification performances, better than a user-defined cutoff. The protocol consists of data preparation and loading, baseline information summarization, parameter tuning, biomarker screening, result visualization and interpretation, biomarker gene annotations, and result and v

SUBMITTER: Feng X 

PROVIDER: S-EPMC6235481 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature