moduleEvals: Shiny Application for Optimal Module Evaluations
In zhouLabNCSU/C3NA: Correlation and Consensus-Based Cross-Taxonomy Network Analysis (C3NA)
moduleEvals R Documentation
Shiny Application for Optimal Module Evaluations
Description
Shiny application that includes two panels. On the first panel, the user can conduct a step-by-step investigation of the consensus-based module selection, and the results will be summarized into an R command in which the user copies and pastes to the R console. The second panel includes a download window for extracting the module pattern, silhouette plot, consensus, and correlation plots.
Usage
moduleEvals(C3NAObj = C3NAObj, colorSeed = 9)
Arguments
C3NAObj
(Required) The C3NAObj with a single phenotype and after the initiateC3NA function.
colorSeed
(Optional) The seed set for reproducible random colors for the bar plot fill. Default: 9.
zhouLabNCSU/C3NA documentation built on Oct. 10, 2022, 4:43 a.m.
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| moduleEvals | R Documentation |
Shiny Application for Optimal Module Evaluations
Description
Shiny application that includes two panels. On the first panel, the user can conduct a step-by-step investigation of the consensus-based module selection, and the results will be summarized into an R command in which the user copies and pastes to the R console. The second panel includes a download window for extracting the module pattern, silhouette plot, consensus, and correlation plots.
Usage
moduleEvals(C3NAObj = C3NAObj, colorSeed = 9)
Arguments
C3NAObj |
(Required) The C3NAObj with a single phenotype and after the initiateC3NA function. |
colorSeed |
(Optional) The seed set for reproducible random colors for the bar plot fill. Default: 9. |
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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