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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 ...
WGCNA is an R package for weighted correlation network analysis. Pigengene is an R package that infers biological information from gene expression profiles. Based on a coexpression network, it computes eigengenes and effectively uses them as features to fit decision trees and Bayesian networks that are useful in diagnosis and prognosis.
The table shown on the right can be used in a two-sample t-test to estimate the sample sizes of an experimental group and a control group that are of equal size, that is, the total number of individuals in the trial is twice that of the number given, and the desired significance level is 0.05. [4]
The concept of gene co-expression networks was first introduced by Butte and Kohane in 1999 as relevance networks. [6] They gathered the measurement data of medical laboratory tests (e.g. hemoglobin level ) for a number of patients and they calculated the Pearson correlation between the results for each pair of tests and the pairs of tests which showed a correlation higher than a certain level ...
Fisher's exact test (also Fisher-Irwin test) is a statistical significance test used in the analysis of contingency tables. [1] [2] [3] Although in practice it is employed when sample sizes are small, it is valid for all sample sizes.
In a random network the maximum degree, or the expected largest hub, scales as k max ~ log N, where N is the network size, a very slow dependence. In contrast, in scale-free networks the largest hub scales as k max ~ ∼N 1/(γ−1) indicating that the hubs increase polynomically with the size of the network.
The MIL-STD-414 provides tables to obtain the required sample size and the critical distance according to the type of inspection. External links. OC curve.
Under pressure from Fisher, Barnard retracted his test in a published paper, [8] however many researchers prefer Barnard’s exact test over Fisher's exact test for analyzing 2 × 2 contingency tables, [9] since its statistics are more powerful for the vast majority of experimental designs, whereas Fisher’s exact test statistics are conservative, meaning the significance shown by its p ...