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2013 arizona-swc

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2013 arizona-swc

  1. 1. Software Carpentry @ Arizona!
  2. 2. Instructors • Titus Brown • Karen Cranston • Rich Enbody • Deren, Chas, Katie, Nirav
  3. 3. What do scientists care about? 1. Correctness 2. Reproducibility and provenance 3. Efficiency
  4. 4. What do scientists actually care about? 1. Efficiency 2. Correctness 3. Reproducibility and provenance
  5. 5. 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
  6. 6. 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.
  7. 7. Automation
  8. 8. 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.
  9. 9. 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

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