GOsummaries-package: Word cloud summaries of GO enrichment analysis
In raivokolde/GOsummaries: Word cloud summaries of GO enrichment analysis
Description
A package to visualize Gene Ontology (GO) enrichment analysis results on gene lists
arising from different analyses such clustering or PCA. The significant GO categories
are visualised as word clouds that can be combined with different plots summarizing
the underlying data.
Details
The goal of GOsummaries package is to draw figures that can be used in
presentations and articles. To draw them, the user should first construct a
gosummaries object and then use its plot function on it. One can start
constructing the gosummaries object from gene lists, with filling in all
the necessary information step by step. However, there are some convenience functions
for different classes of common analysis results. See gosummaries.kmeans,
gosummaries.MArrayLM and gosummaries.prcomp corresponding
to k-means, limma and PCA results.
The plot.gosummaries describes how to customize the plots.
The word cloud drawing function plotWordcloud in this package is
implemented largely based on the code from package wordcloud, but with slight
tweaks: it uses grid graphics, has some additional layout options, has more
intelligent options to scale the text sizes to fit the picture and, finally, should be
a bit faster since larger part of the algorithm was implemeted in C++.
raivokolde/GOsummaries documentation built on May 26, 2019, 9:55 p.m.
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
A package to visualize Gene Ontology (GO) enrichment analysis results on gene lists arising from different analyses such clustering or PCA. The significant GO categories are visualised as word clouds that can be combined with different plots summarizing the underlying data.
Details
The goal of GOsummaries package is to draw figures that can be used in
presentations and articles. To draw them, the user should first construct a
gosummaries object and then use its plot function on it. One can start
constructing the gosummaries object from gene lists, with filling in all
the necessary information step by step. However, there are some convenience functions
for different classes of common analysis results. See gosummaries.kmeans,
gosummaries.MArrayLM and gosummaries.prcomp corresponding
to k-means, limma and PCA results.
The plot.gosummaries describes how to customize the plots.
The word cloud drawing function plotWordcloud in this package is
implemented largely based on the code from package wordcloud, but with slight
tweaks: it uses grid graphics, has some additional layout options, has more
intelligent options to scale the text sizes to fit the picture and, finally, should be
a bit faster since larger part of the algorithm was implemeted in C++.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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