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Reproducibility Tour

Goal

This tutorial is intended to give you a “tour” of how you can build your own reproducible analyses utilizing CyVerse resources. In reality, building a reproducible workflow could take days, weeks, or longer. This short look will point out some tools and resources you can use along your path.

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• Tutorial home
• Intro and Github setup
  • Choose a License
  • Setup a Github Repository
• Computer and project setup with Github, Conda, and the Data Store
  • Connect to the Atmosphere VM
  • Make a local clone of your Github repository
  • Install Conda
  • Install and test JupyterLab
  • Install and test snakemake
  • Install and test Docker
  • Setup your local filesystem
  • Commit to GitHub and copy your work to the Data Store
• Use Biocontainers to assemble your tools
  • Pipeline Description
  • Exploring containers with Biocontainers
  • Combining Biocontainers in a bash script
• Use Snakemake to build your workflow
  • Snakemake example
  • Full Snakemake worfklow
  • Document your work
• Use Jupyter to communicate your results
  • Start Jupyter and begin working through your results

Prerequisites

Downloads, access, and services

In order to complete this tutorial you will need access to the following services/software

Prerequisite	Preparation/Notes	Link/Download
CyVerse account	You will need a CyVerse account to complete this exercise	CyVerse User Portal
Atmosphere access	You must have access to Atmosphere	CyVerse User Portal

Platform(s)

We will use the following CyVerse platform(s):

Platform	Interface	Link	Platform Documentation	Quick Start
Data Store	GUI/Command line	Data Store	Data Store Manual	Data Store Guide
Discovery Environment	Web/Point-and-click	Discovery Environment	DE Manual	Discovery Environment Guide
Atmosphere	Command line (ssh) and/or Desktop (VNC)	Atmosphere	Atmosphere Manual	Atmosphere Guide

Application(s) used

Atmosphere Image(s):

Image name	Version	Description	Link	Notes/other links
Ubuntu 18.04 NoDesktop Base	2.0	Base image with Ubuntu 18.04	Atmosphere Image	Large2 size recommended

Other Installations

Note

In most cases, we will be installing these tools on Atmosphere instances. This tutorial is mostly command line. If using your own computer you will need a terminal already installed on Linux or mac). If you are using Windows, please see the instructions for installing the Windows Linux Subsystem.

Prerequisite	Notes	Links
Docker	Docker is a technology for running individual software tools in a reproducible environment, and on any machine. We request you install The Desktop, Community Edition of Docker if you are using Windows or MacOS. The Docker CE x86_64 instructions are also available for Linux users. If you have installation problems, we will also have backup cloud instances available.	Download Docker
Git	Git is a version control software. If you are using Linux or MacOS, you most likely already have Git. Windows users may need to install Git. You can find instructions for Git installation at the link.	Install Git
Text editor	You will need to have a text editor suitable for working with code (Not Microsoft word, or other word processing software).	We recommend Atom
Jupyter lab	Jupyter is a popular data science workbench for reproducible analysis	Install Juypyter lab
Windows Linux Subsystem (Windows PC only)	This enables using Linux on Windows 10 PCs	We suggested installing the Windows Linux Subsystem if you have a Windows 10 PC. Following the directions we also suggest installing an Ubuntu 18.04 LTS distribution.

Input and example data

In this tutorial, we will be assembling the genome of the protozoan Plasmodium falciparum - the parasite that causes malaria. We will be importing data from the NCBI Sequence Read Archive.

Input File(s)	Format	Preparation/Notes	Example Data
NCBI Sequence read data	NCBI SRA archival file	Files will be imported using NCBI SRA tools	NCBI Experiment Description

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