A General Framework for Weighted Gene Co-Expression Network Analysis

By Bin Zhang, Steve Horvath. Statistical Applications in Genetics and Molecular Biology, 2005

4,882 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/00ae5e12df354c4c70b7d51863c6f9f15e44a46a

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In Molecular Biology

Citations in the corpus

How well do network models predict observations? On the importance of predictability in network models (2016, background): “Solutions could be to determine the topological overlap [38] and choose only one variable in case of large overlap or to incorporate measurement models into the network model [12].”
A method for generating realistic correlation matrices (2011, methodology): “, hierarchical clustering, PAM [22], HOPACH [40], 43 QT clustering [14], WGCNA [43]) use distances in lieu of raw data to partition or 44 agglomerate observations into groups.”
Global Functional Atlas of Escherichia coli Encompassing Previously Uncharacterized Proteins (2009, methodology): “] used to integrate the PI data and the four GC networks. The weighted topological overlap [”
Design and computational analysis of single-cell RNA-sequencing experiments (2016, methodology): “The weighted gene co-expression network analysis (WGCNA) is an analysis approach widely used in bulk RNA-seq [84].”
WGCNA: an R package for weighted correlation network analysis (2008, positive): “For weighted networks, 0 ≤ aij ≤ 1 implies that 0 ≤ ClusterCoefi ≤ 1 [5].”
Clustering in weighted networks (2009, background): “Recently, there have been a number of attempts to extend the local clustering coefficient to the case of weighted networks (Barrat et al., 2004; Lopez-Fernandez, Robles and Gonzalez-Barahona, 2004; Onnela et al., 2005; Zhang and Horvath, 2005).”
Tree-Guided Group Lasso for Multi-Task Regression with Structured Sparsity (2009, methodology): “cent eQTL studies, the expression traits for individual genes were analyzed separately, and then, the results were examined for all genes in light of gene modules to see if any gene sets are enriched for association with a common SNP [Zhu et al. (2008); Emilsson et al.”
G3BP1 is a tunable switch that triggers phase separation to assemble stress granules (2020, positive): “Only physical protein-protein interactions were considered, and the interactome was filtered by edge confidence scores, with thresholds determined by best fitting the scale-free network property (Barabasi and Albert, 1999; Zhang and Horvath, 2005).”
Progranulin Deficiency Promotes Circuit-Specific Synaptic Pruning by Microglia via Complement Activation (2016, methodology): “We used weighted correlation network analysis (WGCNA) to identify highly correlated gene modules that were either up- or downregulated in an age-dependent and genotype-specific manner (Figure 1A) (Langfelder and Horvath, 2008; Zhang and Horvath, 2005).”
Aging effects on DNA methylation modules in human brain and blood tissue (2012, background): “Studies of our group [42,45-48] and of independent groups [49] provide empirical evidence that the topological overlap measure is a biologically meaningful network similarity measure.”
Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology (2011, positive): “We next applied weighted-gene co-expression network analysis (WGCNA) 8; 9 to integrate the expression differences observed between autistic and control cerebral cortex into a higher order, systems level context.”
Statistical Estimation of Correlated Genome Associations to a Quantitative Trait Network (2009, methodology): “Other variations of the standard relevance network have been suggested [31], and any of these QTNs as well as various other methods for learning a QTN can also be used within our proposed regression methods.”