What is a co-expression analysis?
What is a co-expression analysis?
Weighted gene co-expression network analysis (WGCNA) is a bioinformatics application for exploring the relationships between different gene sets (modules), or between gene sets and clinical features (Langfelder and Horvath, 2008).
What are co-expression modules?
Modules or the highly connected subgraphs in gene co-expression networks correspond to clusters of genes that have a similar function or involve in a common biological process which causes many interactions among themselves.
What is the meaning of CO-expression?
Filters. (genetics) The simultaneous expression of two or more genes.
What does it mean if genes are co expressed?
gene co-expression network
A gene co-expression network is a group of genes whose level of expression across different samples and conditions for each sample are similar (Gardner et al., 2003).
What is protein co-expression?
The co-expression of proteins that form a complex. Often the seperate components of a complex are not soluble mostly due to hydrophobic patches that are exposed to the solvent. These patches are usually involved in and protected by the binding to the other component(s) of the complex.
What is an Eigengene?
eigengene (plural eigengenes) (genetics) (mathematics) One of a set of right singular vectors of a genes x samples matrix that tabulates, e.g., the mRNA or gene expression of the genes across the samples.
What are gene modules?
A gene module is defined as a set of coexpressed genes to which the same set of transcription factors binds.
What is module analysis?
An Analysis module is a special QTM project created with Project Automation Framework. Each analysis module is configured with a patient/subject metadata structure, a set of trials, analyses pipelines and report templates.
What is a hub gene?
Hub genes are defined as genes with high correlation in candidate modules. High connectivity means that the connectivity ranked at top 10%. For example, if the module size was 1000, then the genes with top 100 were defined as the hub genes.
How is gene coexpression measured?
One method to infer gene function and gene–disease associations from genome-wide gene expression is co-expression network analysis (Figure 1), an approach that constructs networks of genes with a tendency to co-activate across a group of samples and subsequently interrogates and analyses this network.
Who uses network analysis?
Network analysis is based on graph theory and is widely used in several scientific areas as for example physics, computer science, linguistics and social sciences. In biology, network analysis was applied for example to food webs, social organization and, more recently, to molecular networks (reviewed in [25]).
Where can I find the microarray expression data?
A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide Jonathan D. Wren* Arthritis and Immunology Research Program, Oklahoma Medical Research Foundation;, 825 N.E. 13th Street, Oklahoma City, Oklahoma OK 73104-5005, USA. *To whom correspondence should be addressed.
Which is the best definition of a co-expressed gene?
We define co-expressed genes as genes that share similar expression patterns as discovered by cluster analysis, and we define co-regulated genes as genes that are regulated by at least one common known transcription factor. Our overall approach is illustrated in Figure 1.
What kind of microarray is used to study yeast?
We used two publicly available yeast microarray datasets consisting of hundreds of microarray experiments: the yeast compendium data [ 2] and the yeast environmental stress data [ 15, 16 ].
How does microarray technology enable global view of transcriptome?
Microarray technology has enabled a global view of the transcriptome and created an abundance of data. Most of the analysis tools and methods to date have focused on experiment-centric analysis.