Where to start? (Linked and somewhat expanded from poster but I am trying to keep it reasonably sized and focusing on items with which I am familiar)
Practical Computing for Biologists book by Haddock and Dunn
Bioinformatics Data Skills: Reproducible and Robust Research with Open Source Tools by Vince Buffalo
-
Code in browser. Use Python, but avoid installation hurdle & stay portable. (But, of course, your own compter is good too!)
-
Internet tutorials, blogs, and Coursera or EdX courses.
- Rosalind, platform for learning bioinformatics and programming through problem solving
- Several courses are at Coursera and EdX. (Plus ones for R!) I have experience with several (including some for R) and I'd be happy to discuss them with you in regards to your goals and ambition/time because some can be demanding or most tend to be either algorithm/biological science-slanted or coding in general/computer science-slanted with different suggested prerequisites. Recently Coursera has Python for Genomic Data Science that better spans the two fields with no prerequisites. Python for Genomic Data Science Coursera course is only four weeks and has a good balance of coverage of basics in relation to practical concerns to get you up and scripting in genomics realm pretty fast.
-
Software Carpentry workshops or workshop contents
-
Introduction to coding in Python workshop for January Feng Lab Meeting contains lots of resources
-
Titus Brown’s NGS course resources. (Search ‘ANGUS Titus’ and a year, 2010 to 2015.)
-
Data Carpentry workshops or workshop contents
-
A Data Scientist's Toolbox for ChIP-Seq and Beyond for March 2015 Feng Lab group meeting and Hands-on workshop on ChIP-seq for May 2015 Feng Lab group meeting contain lots of resources and examples to explore as well
-
Explore Galaxy (Less command line & more forms-based.)