Genomics Division, ITER genomicsITER

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Related Setup: https://gist.github.com/hofmannsven/6814278
Related Pro Tips: https://ochronus.com/git-tips-from-the-trenches/
Interactive Beginners Tutorial: http://try.github.io/
Git Cheatsheet by GitHub: https://services.github.com/on-demand/downloads/github-git-cheat-sheet/

Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning

This is just a quick list of resourses on TDA that I put together for @rickasaurus after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.

Survey Papers

Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

Topology and Data by Gunnar Carlsson
Barcodes: The Persistent Topology of Data by Robert Ghrist

Other Papers and Web Resources

Extracting insights from the shape of complex data using topology A good introductory paper in Nature on the Mapper algorithm.

	#!/bin/bash

	set -e
	set -u
	set -o pipefail

	# A script to subsample Fasta/FastQ files using Seqtk
	if ! `command -v seqtk > /dev/null 2> /dev/null`
	then
	echo "Failed to find seqtk!"

	library(ggplot2)

	setwd("<my working directory>")

	removeExtraLine <- function(x) {
	x[,2:length(x)]
	}

	createInitialDataset <- function(x, sampleName) {
	extraLineRemoved <- t(removeExtraLine(x))

	#!/bin/bash
	#$ -V
	#$ -S /bin/bash

	#Embrrassingly Parallel Computations Using the Sun Grid Engine
	#Array Job
	#qsub -pe make 3 -cwd -j y -N hong -t 1-3 test.sh
	#MANIFEST=sample1.txt
	#SAMPLE=`awk "NR==${SGE_TASK_ID}" ${MANIFEST}`
	#echo $SAMPLE