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GeneNet (version 1.2.16)

Modeling and Inferring Gene Networks

Description

Analyzes gene expression (time series) data with focus on the inference of gene networks. In particular, GeneNet implements the methods of Schaefer and Strimmer (2005a,b,c) and Opgen-Rhein and Strimmer (2006, 2007) for learning large-scale gene association networks (including assignment of putative directions).

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Version

Install

install.packages('GeneNet')

Monthly Downloads

872

Version

1.2.16

License

GPL (>= 3)

Last Published

November 14th, 2021

Functions in GeneNet (1.2.16)

cor0.test

Test of Vanishing (Partial) Correlation
network.make.graph

Graphical Gaussian Models: Plotting the Network
kappa2n

Relationship Between Sample Size and the Degree of Freedom of Correlation Distribution
ggm.simulate.data

Graphical Gaussian Models: Simulation of Data
GeneNet-package

The GeneNet package
ecoli

Microarray Time Series Data for 102 E. Coli Genes Genes
GeneNet-internal

Internal GeneNet Functions
ggm.estimate.pcor

Graphical Gaussian Models: Small Sample Estimation of Partial Correlation
ggm.simulate.pcor

Graphical Gaussian Models: Simulation of Networks
arth800

Time Series Expression Data for 800 Arabidopsis Thaliana Genes
network.test.edges

Graphical Gaussian Models: Assess Significance of Edges (and Directions)
z.transform

Variance-Stabilizing Transformations of the Correlation Coefficient