Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection.

ABSTRACT: To understand the difference between benign and severe outcomes after Coronavirus infection, we urgently need ways to clarify and quantify the time course of tissue and immune responses. Here we re-analyze 72-hour time-series microarrays generated in 2013 by Sims and collaborators for SARS-CoV-1 in vitro infection of a human lung epithelial cell line. Transcriptograms, a Bioinformatics tool to analyze genome-wide gene expression data, allow us to define an appropriate context-dependent threshold for mechanistic relevance of gene differential expression. Without knowing in advance which genes are relevant, classical analyses detect every gene with statistically-significant differential expression, leaving us with too many genes and hypotheses to be useful. Using a Transcriptogram-bas

SUBMITTER: de Almeida RMC 

PROVIDER: S-EPMC7310616 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature