Software Carpentry @ Arizona!

Instructors

• Titus Brown• Karen Cranston• Rich Enbody

• Deren, Chas, Katie, Nirav

What do scientists care about?

1. Correctness2. Reproducibility and provenance3. Efficiency

What do scientists actually care about?

1. Efficiency

2. Correctness3. Reproducibility and provenance

Our concern

• As we become more reliant on computational inference, does more of our science become wrong?

• “Big Data” increasingly requires sophisticated computational pipelines…

• We know that simple computational errors have gone undetected for many years– a sign error => retraction of 3 Science, 1 Nature, 1 PNAS– Rejection of grants, publications!

http://boscoh.com/protein/a-sign-a-flipped-structure-and-a-scientific-flameout-of-epic-proportions

Our central thesis

With only a little bit of training and effort,• Computational scientists can become more

efficient and effective at getting their work done,

• while considerably improving correctness and reproducibility of their code.

Automation

Why Python, and not R?

In my opinion,

• Python is a more general purpose language, while R is mostly about data analysis.

• Everyone will need to learn multiple languages; R and Python are pretty dominant in bio right now.

• Luckily, once you get the hang of it, new languages are not so difficult to pick up.

• Ultimately, we’re trying to teach process not details.

Administrivia

• Asking for help

• Using the Web site

• Sticky notes: ok? Not ok?

• Minute cards: at the end of every session, write down

• One thing you learned• One thing you are confused about