Stephen Turner stephenturner

Step 0:

Get Homebrew installed on your mac if you don't already have it

Step 1:

Install highlight. "brew install highlight". (This brings down Lua and Boost as well)

Step 2:

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

Deploying a subfolder to GitHub Pages

Sometimes you want to have a subdirectory on the master branch be the root directory of a repository’s gh-pages branch. This is useful for things like sites developed with Yeoman, or if you have a Jekyll site contained in the master branch alongside the rest of your code.

For the sake of this example, let’s pretend the subfolder containing your site is named dist.

Step 1

Remove the dist directory from the project’s .gitignore file (it’s ignored by default by Yeoman).

Usage

To use these scripts:

Clone this repository: git clone https://gist.github.com/95a4b2ab3b90f6f0bfd9.git snpEffScript
cd snpEffScript
make appropriate changes to setup.sh
call snpEff.sh like so:

	## See http://gettinggeneticsdone.blogspot.com/2013/06/customize-rprofile.html

	## Load packages
	library(BiocInstaller)

	## Don't show those silly significanct stars
	options(show.signif.stars=FALSE)

	## Do you want to automatically convert strings to factor variables in a data.frame?
	## WARNING!!! This makes your code less portable/reproducible.

	idat2lumibatch <- function(filenames) {
	# filenames is a character vector of iDAT filenames
	require(illuminaio)
	require(lumi)
	idatlist = lapply(filenames,readIDAT)
	exprs = sapply(idatlist,function(x) {
	return(x$Quants$MeanBinData)})
	se.exprs = sapply(idatlist,function(x) {
	return(x$Quants$DevBinData/sqrt(x$Quants$NumGoodBeadsBinData))})
	beadNum = sapply(idatlist,function(x) {

	require(reshape2)

	# data.table commit (1048)
	require(data.table)
	# Loading required package: data.table
	# data.table 1.8.11 For help type: help("data.table")

	set.seed(1)
	N <- 2e7 # size of DT

	export SAMPLES="2484-AJ-0001 2484-AJ-0002 2484-AJ-0003"

	######################################
	# Make FASTQ
	######################################
	export OVHOME=/home/arq5x/cphg-home/cphg-quinlan/projects/ov-cell-lines
	export STEPNAME=ovc-fastq
	for sample in `echo $SAMPLES`
	do
	export QSUB="qsub -W group_list=cphg_arq5x -q arq5xlab -V -l select=1:mem=8000m:ncpus=1 -N $STEPNAME -m bea -M [email protected]";

	# A quick function to save a PBM (http://en.wikipedia.org/wiki/Netpbm_format)
	# visualize a lot of missing data pretty quickly (outside of R).

	writeMissingPBM <- function(x, file) {
	dims <- dim(x)
	x[] <- as.integer(is.na(x))
	con <- file(file, open="wt")
	writeLines(sprintf("P1\n%d %d", ncol(x), nrow(x)), con)
	write.table(x, file=con, sep=" ", col.names=FALSE, row.names=FALSE, quote=FALSE)
	close(con)

	rsync -av rsync://ftp.ncbi.nlm.nih.gov/genomes/Bacteria --include "/" --include "Bacteria/Escherichia/.fna" --exclude= .

	# bonus script - concatenate chromosomes and plasmids into single fasta file, make sure the files don't already exist

	find . -mindepth 1 -type d \| xargs -L 1 -I '{}' find {} -name "*.fna" \| while read i ; do cat "$i" >> `dirname "$i"`.fasta ; done