Difference between revisions of "BCB330"
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==Contents== | ==Contents== | ||
| + | |||
| + | * how to maintain a lab journal on Google Docs and MediaWiki | ||
| + | * a bioinformatics centric introduction to R | ||
| + | * uses of GitHub | ||
| + | * collaborative workflow via RStudio, GitHub and back | ||
| + | * best practices for reproducible research (documentation and backup) | ||
| + | * writing and maintaining requirements documents | ||
| + | * architecture-centric design | ||
| + | * defining software module interfaces | ||
| + | * test-driven development (incl. unit- and integration testing) | ||
| + | * code style guides | ||
| + | * function templates | ||
| + | * essentials of code-review | ||
| + | * contributing to R packages | ||
| + | * (possibly: principles of literate programming and R-Notebooks) | ||
| + | * documentation (with Roxygen and markdown) | ||
| + | |||
| + | |||
| + | * design patterns for bioinformatics, and | ||
| + | * simulation and permutation tests for statistics with biological datasets | ||
| + | |||
| + | |||
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==Further reading and resources== | ==Further reading and resources== | ||
<!-- {{#pmid:21627854}} --> | <!-- {{#pmid:21627854}} --> | ||
Revision as of 03:00, 8 May 2017
BCB330Y (Special Project in Bioinformatics and Computational Biology)
BCB430Y (Advanced Special Project in Bioinformatics and Computational Biology)
Summary ...
- http://biochemistry.utoronto.ca/courses/bcb330y-bcb-project/
- http://biochemistry.utoronto.ca/courses/bcb430y-bcb-project/
Introductory reading
Contents
- how to maintain a lab journal on Google Docs and MediaWiki
- a bioinformatics centric introduction to R
- uses of GitHub
- collaborative workflow via RStudio, GitHub and back
- best practices for reproducible research (documentation and backup)
- writing and maintaining requirements documents
- architecture-centric design
- defining software module interfaces
- test-driven development (incl. unit- and integration testing)
- code style guides
- function templates
- essentials of code-review
- contributing to R packages
- (possibly: principles of literate programming and R-Notebooks)
- documentation (with Roxygen and markdown)
- design patterns for bioinformatics, and
- simulation and permutation tests for statistics with biological datasets
Further reading and resources
