Log-Linear Poisson Graphical Model with Hot-Deck Multiple Imputation

Infer log-linear Poisson Graphical Model with an auxiliary data set. Hot-deck multiple imputation method is used to improve the reliability of the inference with an auxiliary dataset. Standard log-linear Poisson graphical model can also be used for the inference and the Stability Approach for Regularization Selection (StARS) is implemented to drive the selection of the regularization parameter. The method is fully described in .


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Infer log-linear Poisson Graphical Model with an auxiliary dataset. Hot-deck multiple imputation method is used to improve the reliability of the inference ith an auxiliary dataset. Standard log-linear Poisson GM can also be used for the inference and the StARS criterion is implemented to drive the selection of the regularization parameter.

See [Citation file] for citation details and the [User's Guide] for an example of usage.

News

Version 0.1.2 remove Biocstyle for vignette formatting (instable links with Bioconductor) updated references with published article


Version 0.1.1 [2017-05-16] new features GLMnetToGraph can now be used with matrices

improved column names of the count data are now included in the result of GLMnetwork

bug fixes fixed two bugs in plot.HDpath

documentation added a vignette and a complete user guide fixed a few typos fixed an imprecise statement in print.GLMpath documentation updated references improved README file


Version 0.1.0 [2017-04-19] Initial release

Reference manual

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install.packages("RNAseqNet")

0.1.2 by Nathalie Villa-Vialaneix, 5 months ago


Browse source code at https://github.com/cran/RNAseqNet


Authors: Alyssa Imbert [aut], Nathalie Villa-Vialaneix [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports igraph, hot.deck, PoiClaClu, glmnet, methods, utils

Depends on ggplot2

Suggests knitr, rmarkdown


See at CRAN