The Bioinformatics Institute, A*STAR

Oct 21-23, 2019

9:00 am - 5:30 pm

Instructors: Ashar J. Malik, Akshita Kumar, Lauren M. Reid, Lee Hwee Kuan, Lee Xiong An, Roland Huber

Helpers: Nguyen Thanh Binh, Shilpa Yadahalli, Wang Dong

General Information

Software 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 programming and plotting with Python and basic programming in R. Additionally considering the need of the time, theory and practices in Machine Learning have also been added to this workshop. 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 who are new to programming. You don't need to have any previous knowledge of the tools that will be presented at the workshop.

Where: Cysteine, #07-01, Matrix, 30 Biopolis Street. Get directions with OpenStreetMap or Google Maps.

When: Oct 21-23, 2019. 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).

Code of Conduct: Everyone who participates in Carpentries activities is required to conform to the Code of Conduct. This document also outlines how to report an incident if needed.

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

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 asharjm@bii.a-star.edu.sg for more information.

Personal Data Protection Notice: By registering for this event, you hereby consent to the collection, use and disclosure of your personal data by the event organizer for the purposes of processing, administering and managing your registration for this event.

Photography and Videography: Photography and videography will take place during the event. By taking part in this event, you are consenting that these images can be used by the event organizer for any form of publicity usage including but not limited to website, media and publication purposes.



Schedule

Day 1

09:00 Building Programs with Python
10:30 Morning break
12:00 Lunch break
13:00 Programming with R
14:30 Afternoon break
16:00 Wrap-up
16:30 END

Day 2

09:00 Plotting with Python
10:30 Morning break
12:00 Lunch break
13:00 Introduction to Machine Learning
14:30 Afternoon break
16:00 Wrap-up
16:40 END

Day 3

09:00 Methods in Machine Learning - I
10:30 Morning break
12:00 Lunch break
13:00 Methods in Machine Learning - II
14:30 Afternoon break
16:00 Wrap-up
16:40 END

Syllabus

Programming in Python

  • Using Libraries
  • Working with Arrays
  • Reading and Plotting Data
  • Creating and Using Functions
  • Loops and Conditionals
  • Defensive Programming
  • Using Python from the Command Line
  • Reference...

Programming in R

  • Working with Vectors and Data Frames
  • Reading and Plotting Data
  • Creating and Using Functions
  • Loops and Conditionals
  • Using R from the Command Line
  • Reference...

Machine Learning

  • TBD

Setup

To participate in a Software 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.

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, hit the Esc key, followed by :+Q+! (colon, lower-case 'q', exclamation mark), then hitting Return to return to the shell.

nano is a basic editor and the default that instructors use in the workshop. It is installed along with Git.

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.

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 BBEdit or Sublime Text.

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.

Python

Python is a popular language for research computing, and great for general-purpose programming as well. Installing all of its research packages individually can be a bit difficult, so we recommend Anaconda, an all-in-one installer.

Regardless of how you choose to install it, please make sure you install Python version 3.x (e.g., 3.6 is fine).

We will teach Python using the Jupyter notebook, a programming environment that runs in a web browser. For this to work you will need a reasonably up-to-date browser. The current versions of the Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9 and below, are not).

  1. Open https://www.anaconda.com/download/#linux with your web browser.
  2. Download the Python 3 installer for Linux.
    (The installation requires using the shell. If you aren't comfortable doing the installation yourself stop here and request help at the workshop.)
  3. Open a terminal window.
  4. Type
    bash Anaconda3-
    and then press Tab. The name of the file you just downloaded should appear. If it does not, navigate to the folder where you downloaded the file, for example with:
    cd Downloads
    Then, try again.
  5. Press Return. You will follow the text-only prompts. To move through the text, press Spacebar. Type yes and press enter to approve the license. Press enter to approve the default location for the files. Type yes and press enter to prepend Anaconda to your PATH (this makes the Anaconda distribution the default Python).
  6. Close the terminal window.

R

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

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.

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.