Weighted correlation network analysis, also known as weighted gene co-expression network analysis (WGCNA), is a widely used data mining method especially for studying biological networks based on pairwise correlations between variables. While it can be applied to most high-dimensional data sets, it has been most widely used in genomic applications. It allows one to define modules (clusters), intramodular hubs, and network nodes with regard to module membership, to study the relationships between co-expression modules, and to compare the network topology of different networks (differential network analysis). WGCNA can be used as a data reduction technique (related to oblique factor analysis), as a clustering method (fuzzy clustering), as a feature selection method (e.g. as gene screening method), as a framework for integrating complementary (genomic) data (based on weighted correlations between quantitative variables), and as a data exploratory technique.[1] Although WGCNA incorporates traditional data exploratory techniques, its intuitive network language and analysis framework transcend any standard analysis technique. Since it uses network methodology and is well suited for integrating complementary genomic data sets, it can be interpreted as systems biologic or systems genetic data analysis method. By selecting intramodular hubs in consensus modules, WGCNA also gives rise to network based meta analysis techniques.[2]
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Weightedcorrelationnetworkanalysis, also known as weighted gene co-expression networkanalysis (WGCNA), is a widely used data mining method especially...
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accurate molecular biomarker of aging, and for developing weightedcorrelationnetworkanalysis. His work on the genomic biomarkers of aging, the aging...
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commercial suits; network-based approaches for analyzing high dimensional genomic data sets. For example, weightedcorrelationnetworkanalysis is often used...
523–41. Julian C. Stanley, "II. Analysis of Variance," pp. 541–554. Lindley, D.V. (1987). "Regression and correlationanalysis," New Palgrave: A Dictionary...
system. Weighted graphs that blend an abstract understanding of complex network theories and electric power systems properties. Social networkanalysis examines...
Social networkanalysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures...
evaluating similarity in gene expression networks, and is often used for weightedcorrelationnetworkanalysis. Biweight midcorrelation has been implemented...
calibration problem Cancer cluster Candlestick chart Canonical analysis Canonical correlation Canopy clustering algorithm Cantor distribution Carpet plot...
ISSN 0096-851X. Tryon, Robert C. (1939). Cluster Analysis: Correlation Profile and Orthometric (factor) Analysis for the Isolation of Unities in Mind and Personality...
of a slightly different matrix. PCA is also related to canonical correlationanalysis (CCA). CCA defines coordinate systems that optimally describe the...
Components" which are, actually, the eigenvectors of the data correlation matrix weighted by the inverse of their eigenvalues. This change of variables...
spatial neural networks, but they do not consistently handle the spatial heterogeneity at multiple scales. Geographically Weighted Neural Networks (GWNNs) are...
Yang JJ, Chen S, et al. (January 2018). "Application of Weighted Gene Co-expression NetworkAnalysis for Data from Paired Design". Scientific Reports. 8 (1):...
and procedures are: Analysis of variance (ANOVA) Chi-squared test Correlation Factor analysis Mann–Whitney U Mean square weighted deviation (MSWD) Pearson...
to interpret neural network results by analysis of correlations between data cases in the space of models. A physical neural network includes electrically...
regarding its methodology. These criticisms led to the use of the correlation-weighted Kolmogorov–Smirnov test, the normalized ES, and the false discovery...
intercrosses and heterogeneous stock Weightedcorrelationnetworkanalysis, also known as WGCNA Cytoscape network display Correlated trait loci mapping...
semantic networks. In the case of network activity, the analysis is based on partial correlations. In simple words, the partial (or residual) correlation is...
such a network architecture does not take the spatial structure of the data into account. Convolutional networks exploit spatially local correlation by enforcing...
M. (1994). "Analysis of correlation structure for a neural predictive model with applications to speech recognition". Neural Networks. 7 (2): 331–339...
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