Simple method for cutoff point identification in descriptive high-throughput biological studies.

ABSTRACT:

Background

Rapid development of high-throughput omics technologies generates an increasing interest in algorithms for cutoff point identification. Existing cutoff methods and tools identify cutoff points based on an association of continuous variables with another variable, such as phenotype, disease state, or treatment group. These approaches are not applicable for descriptive studies in which continuous variables are reported without known association with any biologically meaningful variables.

Results

The most common shape of the ranked distribution of continuous variables in high-throughput descriptive studies corresponds to a biphasic curve, where the first phase includes a big number of variables with values slowly growing with rank and the second phase includes a smal

SUBMITTER: Suvorov A 

PROVIDER: S-EPMC8922865 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature