Screening of Gene Expression Markers for Corona Virus Disease 2019 Through Boruta_MCFS Feature Selection.

ABSTRACT: Since the first report of SARS-CoV-2 virus in Wuhan, China in December 2019, a global outbreak of Corona Virus Disease 2019 (COVID-19) pandemic has been aroused. In the prevention of this disease, accurate diagnosis of COVID-19 is the center of the problem. However, due to the limitation of detection technology, the test results are impossible to be totally free from pseudo-positive or -negative. Improving the precision of the test results asks for the identification of more biomarkers for COVID-19. On the basis of the expression data of COVID-19 positive and negative samples, we first screened the feature genes through ReliefF, minimal-redundancy-maximum-relevancy, and Boruta_MCFS methods. Thereafter, 36 optimal feature genes were selected through incremental feature selection method base

SUBMITTER: Sun Y 

PROVIDER: S-EPMC9258782 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature