Gene coexpression network analysis is a commonly used approach in bioinformatics and biomedical research to construct coexpression networks and detect coexpressed genes. This type of analysis has proven valuable for gene function prediction and for disease biomarker discovery.Here, we introduce and guide researchers through a method of differential coexpression analysis focusing on key autophagy and metabolic genes. We utilized the open-source Cancer Cell Line Encyclopedia (CCLE ) project as this is one of the most comprehensive genomic and transcriptomic resources including more than 1000 cell lines of distinct origins. However, the coexpression analysis method described here can also be applied to any open-source dataset where the RNA expression are provided.We here provide detailed comprehensive practical instructions for investigators to successfully identify novel coexpression signatures.
Keywords: Autophagy; CCLE; Cancer metabolism; Correlation; Glycolysis; Lung cancer; Pearson; Spearman; The cancer cell line encyclopedia.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.