Linking Cell Dynamics With Gene Coexpression Networks to Characterize Key Events in Chronic Virus Infections.

ABSTRACT: The host immune response against infection requires the coordinated action of many diverse cell subsets that dynamically adapt to a pathogen threat. Due to the complexity of such a response, most immunological studies have focused on a few genes, proteins, or cell types. With the development of "omic"-technologies and computational analysis methods, attempts to analyze and understand complex system dynamics are now feasible. However, the decomposition of transcriptomic data sets generated from complete organs remains a major challenge. Here, we combined Weighted Gene Coexpression Network Analysis (WGCNA) and Digital Cell Quantifier (DCQ) to analyze time-resolved mouse splenic transcriptomes in acute and chronic Lymphocytic Choriomeningitis Virus (LCMV) infections. This enabled us to genera

SUBMITTER: Pedragosa M 

PROVIDER: S-EPMC6509617 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature