SuMO-Fil: Supervised multi-omic filtering prior to performing network analysis.

ABSTRACT: Multi-omic analyses that integrate many high-dimensional datasets often present significant deficiencies in statistical power and require time consuming computations to execute the analytical methods. We present SuMO-Fil to remedy against these issues which is a pre-processing method for Supervised Multi-Omic Filtering that removes variables or features considered to be irrelevant noise. SuMO-Fil is intended to be performed prior to downstream analyses that detect supervised gene networks in sparse settings. We accomplish this by implementing variable filters based on low similarity across the datasets in conjunction with low similarity with the outcome. This approach can improve accuracy, as well as reduce run times for a variety of computationally expensive downstream analyses. This meth

SUBMITTER: Towle-Miller LM 

PROVIDER: S-EPMC8330944 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature