"Simple Tidy GeneCoEx": A gene co-expression analysis workflow powered by tidyverse and graph-based clustering in R
Chenxin Li1, Natalie C Deans1, C Robin Buell1,2,3
1Center for Applied Genetic Technologies, University of Georgia, Athens, Georgia, USA.
None:
Gene co-expression analysis is an effective method to detect groups (or modules) of co-expressed genes that display similar expression patterns, which may function in the same biological processes. Here, we present "Simple Tidy GeneCoEx", a gene co-expression analysis workflow written in the R programming language. The workflow is highly customizable across multiple stages of the pipeline including gene selection, edge selection, clustering resolution, and data visualization. Powered by the tidyverse package ecosystem and network analysis functions provided by the igraph package, the workflow detects gene co-expression modules whose members are highly interconnected. Step-by-step instructions with two use case examples as well as source code are available at https://github.com/cxli233/SimpleTidy_GeneCoEx.
Related Concept Videos
02:34DNA Microarrays
01:42What is Gene Expression?
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
01:29Coordination of Gene Expression Processes in Bacteria
02:02Genomics