linkspotter (version 1.3.0)

linkspotterOnFile: Process Linkspotter on an external file

Description

This function imports an external dataset, computes its correlation matrices, variable clustering and the customizable user interface to visualize them using a graph.

Usage

linkspotterOnFile(
  file,
  corMethods = c("pearson", "spearman", "kendall", "mic", "MaxNMI"),
  defaultMinCor = 0.3,
  defaultCorMethod = corMethods[length(corMethods)],
  clusteringCorMethod = corMethods[length(corMethods)],
  nbCluster = 1:9,
  printInfo = T,
  appTitle = "Linkspotter",
  htmlTop = "",
  htmlBottom = "",
  ...
)

Arguments

file

the file containing a structured dataset which the bivariate correlations are to be analyzed.

corMethods

a vector of correlation coefficients to compute. The available coefficients are the following : c("pearson","spearman","kendall","mic","distCor","MaxNMI"). It is not case sensitive and still work if only the beginning of the word is put (e.g. pears).

defaultMinCor

a double between 0 and 1. It is the minimal correlation absolute value to consider for the first graph plot.

defaultCorMethod

a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the first graph plot.

clusteringCorMethod

a string. One of "pearson","spearman","kendall","mic", "distCor" or "MaxNMI". It is the correlation coefficient to consider for the variables clustering.

nbCluster

an integer. It is the number of clusters to compute.

printInfo

a boolean indicating whether to print on the console some information about the dataset and the estimated computation time.

appTitle

a string taken as the title of the user interface.

htmlTop

a character string that enable to customize your shiny app by adding an HTML code in the HEAD tag.

htmlBottom

a character string that enable to customize your shiny app by adding an HTML code at the end of the BODY tag.

...

Further arguments to be passed to the used read.csv function.

Value

a list containing all the material enabling to analyze correlations:

• computationTime: a string

• run_it: a shiny.appobj object enable to deploy instantly the user interface for a customizable visualization.

• dataset: the initial dataset

• corDF: a the correlation data.frame including values for all coefficients

• corMatrices: a list of correlation matrices

• corGroups: data.frame a data.frame list

• clusteringCorMethod: a character

• defaultMinCor: a numeric

• defaultCorMethod: a string

• corMethods: vector of strings

Examples

# NOT RUN {
# run linkspotter on iris example data
data(iris)
tmpCSV<-tempfile(fileext = '.csv')
write.csv(iris, tmpCSV, row.names = FALSE)
lsOutputIrisFromFile<-linkspotterOnFile(file=tmpCSV)
summary(lsOutputIrisFromFile)
# }
# NOT RUN {
# launch the UI
lsOutputIrisFromFile$launchShiny(options=list(port=8000))
# }
# NOT RUN {
# }