Intro to Genomics Data Wrangling

Berkeley Institute for Data Science

August 6-7, 2018

9:15 am - 5:30 pm

Instructors: Caroline Cypranowska, Diya Das

Helpers: Jenna Baughman, Drew Hart, Dennis Sun

Registration

This workshop is one of three workshops offered at BIDS. Please register for only one, as space is limited.

Registration is mandatory for attendance. We are unable to accept participants who do not have a ticket from Eventbrite (i.e. no drop-ins).

General Information

Data Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including program design, version control, data management, and task automation. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.

For more information on what we teach and why, please see our paper "Best Practices for Scientific Computing".

Who: The course is aimed at graduate students and other researchers at UC Berkeley. Participants from outside the university are welcome to join as long as the Eventbrite permits, for reasons of capacity. However, there is a slight chance that the cloud computing session may not be accessible to you, as it focuses on resources made available by Berkeley Research Computing.

The workshop material is presented at an introductory level, and we will assume that you will not have any previous knowledge of the tools that will be presented at the workshop. The goal of the workshop is to provide learners new to these tools with a basis for further exploration. If you are already familiar with some of these tools, we instead encourage you to check out our peer learning group.

Where: 190 Doe Library, University of California, Berkeley. Get directions with OpenStreetMap or Google Maps.

When: August 6-7, 2018. Add to your Google Calendar.

Requirements: Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. They should have a few specific software packages installed (listed below). They are also required to abide by Data Carpentry's Code of Conduct.

Accessibility: We are committed to making this workshop accessible to everybody. The workshop organizers have checked that:

The room is wheelchair / scooter accessible.
Accessible restrooms are available.

Here is a map of the first floor of Doe Library with restrooms and the accessible entrance marked, from BIDS:

Materials will be provided in advance of the workshop and large-print handouts are available if needed by notifying the organizers in advance. If we can help making learning easier for you (e.g. sign-language interpreters, lactation facilities) please get in touch (using contact details below) and we will attempt to provide them.

Contact: Please email cypranowska@gmail.com or diyadas@berkeley.edu for more information.

Schedule (work in progress)

Surveys

Please be sure to complete these surveys before and after the workshop.

Pre-workshop Survey

Post-workshop Survey

Day 1

9:30 am	Introduction to Data Carpentry
10:00 am	Genomics Organization
11:15 am	Coffee break
11:30 am	Genomics with the Shell
1:00 pm	Lunch break (on your own)
2:00 pm	Genomics with the Shell, cont'd
3:30 pm	Coffee break
3:45 pm	Genomics with the Shell, cont'd
5:00 pm	Wrap up

Day 2

9:30 am	Wrangling Genomics Data
11:15 am	Coffee break
11:30 am	Wrangling Genomics Data, cont'd
1:00 pm	Lunch break (on your own)
2:00 pm	Wrangling Genomics Data, cont'd
3:00 pm	Data manipulation in R
3:30 pm	Coffee break
3:45 pm	Data manipulation in R, cont'd
4:30 pm	Intro to using Savio
5:30 pm	Wrap up

Syllabus (work in progress)

Genomics Project Organization

Data tidiness
Planning NGS Projects
Examining Data on NCBI SRA database

The Unix Shell

Files and directories
Pipes and redirection
Creating and running shell scripts
Organizing filesystems for bioinformatics projects
Reference...

Wrangling Genomics Data

Assessing Read Quality
Trimming and Filtering Reads
Variant Calling
Automation

Programming in R for Genomics

Working with data frames
Using the dplyr package
Data visualization

Setup

To participate in a Data Carpentry workshop, you will need access to the software described below. In addition, you will need an up-to-date web browser.

We maintain a list of common issues that occur during installation as a reference for instructors that may be useful on the Configuration Problems and Solutions wiki page.

Data

The data for this workshop can be accessed through an Amazon Machine Image or downloaded to your local machine, however the data are quite large. Basic instructions for launching a cloud instance can be found here, and instructions for using the AMI instance for this workshop can be found here.

To download the data locally use this link: https://osf.io/ycu8j/

Be aware these data are quite large (~51 GB). The data are organized into two directories:

dc_sample_data (124K)
.dc_sampledata_lite(51GB)

The Bash Shell

Bash is a commonly-used shell that gives you the power to do simple tasks more quickly.

Windows

Video Tutorial

Download the Git for Windows installer.
Run the installer and follow the steps bellow:
1. Click on "Next".
2. Click on "Next".
3. Keep "Use Git from the Windows Command Prompt" selected and click on "Next". If you forgot to do this programs that you need for the workshop will not work properly. If this happens rerun the installer and select the appropriate option.
4. Click on "Next".
5. Keep "Checkout Windows-style, commit Unix-style line endings" selected and click on "Next".
6. Keep "Use Windows' default console window" selected and click on "Next".
7. Click on "Install".
8. Click on "Finish".
If your "HOME" environment variable is not set (or you don't know what this is):
1. Open command prompt (Open Start Menu then type cmd and press [Enter])
2. Type the following line into the command prompt window exactly as shown:
  setx HOME "%USERPROFILE%"
3. Press [Enter], you should see SUCCESS: Specified value was saved.
4. Quit command prompt by typing exit then pressing [Enter]

This will provide you with both Git and Bash in the Git Bash program.

macOS

The default shell in all versions of macOS is Bash, so no need to install anything. You access Bash from the Terminal (found in /Applications/Utilities). See the Git installation video tutorial for an example on how to open the Terminal. You may want to keep Terminal in your dock for this workshop.

Linux

The default shell is usually Bash, but if your machine is set up differently you can run it by opening a terminal and typing bash. There is no need to install anything.

Software

Software	Install	Manual	Available for	Description
FastQC	Link	Link	Linux, MacOS, Windows	Quality control tool for high throughput sequence data.
Trimmomatic	Link	Link	Linux, MacOS, Windows	A flexible read trimming tool for Illumina NGS data.
BWA	Link	Link	Linux, MacOS	Mapping DNA sequences against reference genome.
SAMtools	Link	Link	Linux, MacOS	Utilities for manipulating alignments in the SAM format.
BCFtools	Link	Link	Linux, MacOS	Utilities for variant calling and manipulating VCFs and BCFs.
IGV	Link	Link	Linux, MacOS, Windows	Visualization and interactive exploration of large genomics datasets.

Installing from the terminal

Most of these software packages can be installed using conda or brew. Instructions for installing from the command line (including from source) can be found here.

Text Editor

When you're writing code, it's nice to have a text editor that is optimized for writing code, with features like automatic color-coding of key words. The default text editor on macOS and Linux is usually set to Vim, which is not famous for being intuitive. if you accidentally find yourself stuck in it, try typing the escape key, followed by :q! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

Windows

Video Tutorial

nano is a basic editor and the default that instructors use in the workshop. To install it, download the Data Carpentry Windows installer and double click on the file to run it. This installer requires an active internet connection.

Others editors that you can use are Notepad++ or Sublime Text. Be aware that you must add its installation directory to your system path. Please ask your instructor to help you do this.

macOS

nano is a basic editor and the default that instructors use in the workshop. See the Git installation video tutorial for an example on how to open nano. It should be pre-installed.

Others editors that you can use are Text Wrangler or Sublime Text.

Linux

nano is a basic editor and the default that instructors use in the workshop. It should be pre-installed.

Others editors that you can use are Gedit, Kate or Sublime Text.

R

R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis. To interact with R, we use RStudio.

Windows

Video Tutorial

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select "Run as administrator" instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

macOS

Video Tutorial

Install R by downloading and running this .pkg file from CRAN. Also, please install the RStudio IDE.

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo dnf install R). Also, please install the RStudio IDE.