Thomas Falk reinholdsson

Slidify now allows you to publish your slide decks as gists. You will need the dev version of slidify to use this feature.

require(devtools)
install_github(c('slidify', 'slidifyLibraries'), 'ramnathv', ref = 'dev')

Let us first create a directory for our slide deck and open an index.Rmd file to author our presentation.

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)

MOVED TO: https://delicious.com/reinholdsson

Programming Links

Primarily R and JavaScript links. Collection maintained by Thomas Reinholdsson.

--- Todo: Move to github page and structure up ---

Unsorted

Implementing a DPU with OpenCPU

	# Helper functions that allow string arguments for dplyr's data modification functions like arrange, select etc.
	# Author: Sebastian Kranz

	# Examples are below

	#' Modified version of dplyr's filter that uses string arguments
	#' @export
	s_filter = function(.data, ...) {
	eval.string.dplyr(.data,"filter", ...)
	}

	def shellout(template, **kwargs):
	"""
	Takes a shell command template and executes it. The template must use
	the new (2.6+) format mini language. `kwargs` must contain any defined
	placeholder, only `output` is optional.
	Raises RuntimeError on nonzero exit codes.

	Simple template:

	wc -l < {input} > {output}

	.Rproj.user
	.Rhistory
	.RData
	*.Rproj
	*.html

	#!/usr/bin/Rscript

	require(knitr)
	lf <- commandArgs(trailingOnly = TRUE)
	if(!length(lf))
	lf = list.files(pattern="\\.rmd")
	for (f in lf)
	try(knit(f))

	md = paste0(sub("\\.[[:alnum:]]*$", "", lf), ".md")

	from bubbles import Pipeline, open_store

	stores = {
	"source": open_store("csv", "data/source", encoding="utf16", infer_fields=True),
	"target": open_store("sql", "sqlite:///data.sqlite")
	}

	p = Pipeline(stores=stores)

	# Load customers into a SQL table

	# We first start by creating a way of escaping the characters that have special
	# meaning for html, while making sure we don't end up double-escaping at any
	# point. The easiest way to do this is to create an S3 class that allows us to
	# distinguish between regular text (that needs escaping) and html (that
	# doesn't).
	#
	# We then write an escape method that leaves html unchanged and escapes the
	# special characters (&, <, >) in ordinary text. We also add a method for lists
	# for convenience

	max_plots <- 5

	ui <- fluidPage(

	headerPanel("Dynamic number of plots"),

	sidebarPanel(
	sliderInput("n", "Number of plots", value=1, min=1, max=5)
	),