Lecture Lab 7

Collaborative Bio Data Science using GitHub via RStudio

• When doing assignments, you discovered that it was challenging to collaborate

• Collaboration is key to success, also when coding!

• You could:

  • Write your code in a google doc and copy/paste
  • Send code snippets in emails
  • Use a whatsapp-group to exchange code
  • …?

Collaborative Bio Data Science using GitHub via RStudio

• When doing assignments, you discovered that it was challenging to collaborate

• Collaboration is key to success, also when coding!

• You could:

  • Write your code in a google doc and copy/paste
  • Send code snippets in emails
  • Use a whatsapp-group to exchange code
  • Stare at the same screen and come with 17 suggestions
  • …?

• All of which would be a recipe for inevitable disaster!

Collaborative Bio Data Science using GitHub via RStudio

• Of course there is a better way!

• We can use… git!

• Git is a distributed version control system

• It tracks versions of files

• “Git is a distributed version control system that tracks versions of files. It is often used to control source code by programmers who are developing software collaboratively.” (Wiki definition)

Collaborative Bio Data Science using GitHub via RStudio

• Of course there is a better way!

• We can use… git!

• Git is a distributed version control system

• It tracks versions of files

• “Git is a distributed version control system that tracks versions of analyses. It is often used to control analysis code by bioinformaticians who are developing pipelines collaboratively.” (R4BDS definition)

Collaborative Bio Data Science using GitHub via RStudio

• Bonus info: The brain child of… Linus Torvalds

• Tracking changes in the Linux kernel

Okay, so… Git versus GitHub

• Think along the lines of R versus RStudio, engine and interface

Okay, so… What does it “do”?

• If you share code in mails, chat groups, shared docs

• You have no way of tracking what happened when to what and how

• You may sit with some results and have no idea how they came about

• This is the absolute opposite of doing reproducible bio data science

Okay, so… What does it “do”?

• Git and github:

  • helps you track the EXACT changes made in your analysis project

  • enables multiple collaborators

  • are industry standard in largely any company doing (Bio) Data Science

  • facilitates teamwork increasing productivity

• Again: Spend time initially to save time in the long run

• Remember the talk from the first lab? Using git is absolute key to doing reproducible research

Okay, so… What does it “do”?

…and perhaps nearer to you for now

Okay, so… How does your team “do” it?

Branching, a way of developing in parallel

But really, the best thing is to…

But really, the best thing is to…

• Try it out for your self

• Break and then exercises

• TODAY FOLLOWING THE EXERCISES POINT-BY-POINT IS SUPERCALIFRAGILISTICEXPIALIDOCIOUS!!!