Stuart Lee sa-lee

This is a plain-text version of Bret Victor’s reading list. It was requested by hf on Hacker News.

Highly recommended things!

This is my five-star list. These are my favorite things in all the world.

A few of these works have had an extraordinary effect on my life or way of thinking. They get a sixth star. ★

The introduction to Reactive Programming you've been missing

If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.

duplicates = multiple editions

My first Bioconductor meeting, and I'm not a BioC or R expert so these notes are probably going to be naïve!

	#!/bin/bash

	# check commands: slopBed, bedGraphToBigWig and bedClip

	which bedtools &>/dev/null \|\| { echo "bedtools not found! Download bedTools: <http://code.google.com/p/bedtools/>"; exit 1; }
	which bedGraphToBigWig &>/dev/null \|\| { echo "bedGraphToBigWig not found! Download: <http://hgdownload.cse.ucsc.edu/admin/exe/>"; exit 1; }
	which bedClip &>/dev/null \|\| { echo "bedClip not found! Download: <http://hgdownload.cse.ucsc.edu/admin/exe/>"; exit 1; }

	# end of checking

	# Randomly allocating observations into groups, for, e.g. cross-validation
	kk <- 10 # Number of partitions, as in "kk-fold cross-validation."

	# Here is a data.frame full of good data:
	nn <- 1003
	myData <- data.frame(matrix(rnorm(nn * 3), ncol = 3))
	colnames(myData) <- LETTERS[1:3]

	# This does not work:
	whichK <- sample(LETTERS[1:kk], nrow(myData), replace = T)

	data_sets <- c("mtcars", "morley", "rock")

	shinyServer(function(input, output) {

	# Drop-down selection box for which data set
	output$choose_dataset <- renderUI({
	selectInput("dataset", "Data set", as.list(data_sets))
	})

	# Check boxes

	n <- 200
	m <- 40
	set.seed(1)
	x <- runif(n, -1, 1)
	library(rafalib)
	bigpar(2,2,mar=c(3,3,3,1))
	library(RColorBrewer)
	cols <- brewer.pal(11, "Spectral")[as.integer(cut(x, 11))]
	plot(x, rep(0,n), ylim=c(-1,1), yaxt="n", xlab="", ylab="",
	col=cols, pch=20, main="underlying data")

	accession2url <- function(x) {
	prefix <- "ftp://ftp.sra.ebi.ac.uk/vol1/fastq"
	dir1 <- paste0("/",substr(x,1,6))
	dir2 <- ifelse(nchar(x) == 9, "",
	ifelse(nchar(x) == 10, paste0("/00",substr(x,10,10)),
	ifelse(nchar(x) == 11, paste0("/0",substr(x,10,11)),
	paste0("/",substr(x,10,12)))))
	paste0(prefix,dir1,dir2,"/",x)
	}

	# what dominates PC1: 100 features with 10x fold change or 1 feature with 2x fold change?

	mat <- rbind(matrix(rpois(8*100,rep(c(10,100),each=4)),ncol=8,byrow=TRUE),
	rpois(8,rep(c(1000,1000,2000,2000),2)))
	plot(prcomp(t(mat))$x[,1])