ctsGEShinyApp: GUI for interactive exploration of gene expression data.

In michmich76/ctsGE: Clustering of Time Series Gene Expression data

Description

Produce and launch Shiny app for interactive exploration of gene expression data. For more information about shiny apps http://shiny.rstudio.com/

Usage

ctsGEShinyApp(rts, min_cutoff = 0.5, max_cutoff = 0.7, mad.scale = TRUE,
  title = NULL)

Arguments

rts	list of an expression data that made by readTSGE
min_cutoff	A numeric the lower limit range to calculate the optimal cutoff for the data, default to 0.5 See PreparingTheIndexes.
max_cutoff	A numeric the upper limit range to calculate the optimal cutoff for the data, default to 0.7 See PreparingTheIndexes.
mad.scale	A boolean defaulting to TRUE as to what method of scaling to use. Default median-base scaling. FALSE, mean-base scaling
title	Character, the title at the header panel. default to NULL.

Details

The 'ctsGEShinyApp' function takes the ctsGE object and opens an html page as a GUI. On the web page, the user chooses the profile to visualize and the number of clusters (k parameter for K-means) to show. The line graph of the profile separated into the clusters will show in the main panel, and a list of the genes and their expressions will also be available. The tables and figures can be downloaded.

Value

Creates a shiny application and opens a shinyapp.io web page

See Also

shiny::ShinyApp

Examples

## Not run: 
data_dir <- system.file("extdata", package = "ctsGE")
files <- dir(path=data_dir,pattern = "\\.xls$")
rts <- readTSGE(files, path = data_dir,
labels = c("0h","6h","12h","24h","48h","72h") )
ctsGEShinyApp(rts)
## End(Not run)

michmich76/ctsGE documentation built on May 22, 2019, 9:55 p.m.