trestletech

.Rproj.user
.Rhistory
.RData
transactions/
budgets/

trestletech

setup.sh
token

trestletech

import java.io.FileNotFoundException;
import java.io.FileOutputStream;
import java.io.PrintStream;

public class Main {
    public static void main(String[] args){

        try{
            //Write out to file assuming IntelliJ project layout.
            PrintStream out = new PrintStream(new FileOutputStream("src/timing.txt"));

trestletech

require(shiny)

shinyServer(function(input, output) {
  
  val <- reactive({
    if(input$change>0) {
      # Option 1
       'abc'
      #       # Option 2
      #       isolate({

trestletech

Bioconductor Shiny Example #1

Simple app comparing the expression of genes between Tumor and Normal tissue.

This is an example Shiny app featuring some basic analysis of Ovarian Cancer gene expression data collected on the Affymetrix U133A platform. We filter the available genes and samples down to a much smaller matrix to make reproducibility simpler for a broader audience. The R code involved in sampling the data is available in this Gist as an R-Markdown file, and the sampled data are available in this Gist as Rds files.

To run the application, install shiny (install.packages("shiny")) then run the following command:

library(shiny)

trestletech

Bioconductor Shiny Example #2

A demonstration of Shiny's text widget support.

This is an example Shiny app featuring some basic analysis of Ovarian Cancer gene expression data collected on the Affymetrix U133A platform. We filter the available genes and samples down to a much smaller matrix to make reproducibility simpler for a broader audience. The R code involved in sampling the data is available in this Gist as an R-Markdown file, and the sampled data are available in this Gist as Rds files.

To run the application, install shiny (install.packages("shiny")) then run the following command:

library(shiny)

trestletech

Bioconductor Shiny Example #3

Simple app showing the relationship between a gene's expression and survival.

This is an example Shiny app featuring some basic analysis of Ovarian Cancer gene expression data collected on the Affymetrix U133A platform. We filter the available genes and samples down to a much smaller matrix to make reproducibility simpler for a broader audience. The R code involved in sampling the data is available in this Gist as an R-Markdown file, and the sampled data are available in this Gist as Rds files.

To run the application, install shiny (install.packages("shiny")) then run the following command:

library(shiny)

trestletech

Bioconductor Shiny Example #4

Example Shiny App showing an example of being embedded in a larger, non-Shiny workflow.

This is an example Shiny app featuring some basic analysis of Ovarian Cancer gene expression data collected on the Affymetrix U133A platform. We filter the available genes and samples down to a much smaller matrix to make reproducibility simpler for a broader audience. The R code involved in sampling the data is available in this Gist as an R-Markdown file, and the sampled data are available in this Gist as Rds files.

To run the application, install shiny (install.packages("shiny")) then run the following command:

library(shiny)

trestletech

getLocalGist <- function(gistID, dirName){
  url <- paste0("https://gist.github.com/",gistID,"/download")
  if (shiny:::download(url, paste0(dirName,".tar.gz"), mode = "wb", quiet = TRUE) != 0)
    stop("Failed to download URL ", url)
  
  gistName <- shiny:::untar2(paste0(dirName,".tar.gz"), list=TRUE)[1]
  shiny:::untar2(paste0(dirName,".tar.gz"))
  
  #file.rename seems to be pretty fragile, but this seems to be working...
  dir.create(dirName)

trestletech

library(shiny)


shinyServer(function(input, output) {
 dataset = reactive({

    infile = input$file1  


    if (is.null(infile))