My friend and I () are pleased to announce the release of (0.1.0): a new Shiny application (and Shiny gadget) for creating interactive cluster heatmaps. shinyHeatmaply is based on the R package which strives to make it easy as possible to create interactive cluster .
The app introduces a functionality that a self contained copy of the htmlwidget as an html file with your data and specifications you set from the UI, so it can be embedded in webpages, blogposts and online web appendices for academic publications.
You can see some of ‘s capabilities in the following 40 seconds video:
Running the app/gadget
The application has an import interface as part of the application which currently supports csv, txt, tab, xls, xlsx, rd, rda. You can start the app using:
library(shiny) library(heatmaply) # If you didn't get shinyHeatmaply yet, you can run it through github: # runGitHub("yonicd/shinyHeatmaply",subdir = 'inst/shinyapp') # or just use your locally installed package: library(shinyHeatmaply) runApp(system.file("shinyapp", package = "shinyHeatmaply"))
The gadget is called from the R console and accepts input arguments. The object defined as the input to the shinyHeatmaply gadget is a data.frame or a list of data.frames. You can start it using the following code:
library(shinyHeatmaply) #single data.frame data(mtcars) launch_heatmaply(mtcars) #list data(iris) launch_heatmaply(list('Example1'=mtcars,'Example2'=iris))
牵手常德棋牌官方下载You can see an example of . Or view the following iframe:
We would love to get your feedback!
For or feature requests, please visit the .
Post post credit:牵手常德棋牌官方下载 shinyHeatmaply was made thanks to the dedication of , and based on recent features added to heatmaply by . I am very grateful to them both. This could also not be made possible by the amazing work of the RStudio’s team on , and of on . And lastly, to my adviser for his support and advices.