Recognition of Immune Cell Markers of COVID-19 Severity with Machine Learning Methods.

ABSTRACT: COVID-19 is hypothesized to be linked to the host's excessive inflammatory immunological response to SARS-CoV-2 infection, which is regarded to be a major factor in disease severity and mortality. Numerous immune cells play a key role in immune response regulation, and gene expression analysis in these cells could be a useful method for studying disease states, assessing immunological responses, and detecting biomarkers. Here, we developed a machine learning procedure to find biomarkers that discriminate disease severity in individual immune cells (B cell, CD4⁺ cell, CD8⁺ cell, monocyte, and NK cell) using single-cell gene expression profiles of COVID-19. The gene features of each profile were first filtered and ranked using the Boruta feature selection method and mRM

SUBMITTER: Chen L 

PROVIDER: S-EPMC9073549 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature