SpeedUpR

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Tutorial Code from PLOS Computation Biology Educational Piece on Efficiency in R

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# SpeedUpR

### Quicklinks

-   [Tutorial code](#tutorial-code)
    -   [Abstract](#Abstract)
    -   [The online code files](#the-online-code-files-from-s1-text)
-   [Workshop](#workshop)
    -   [code](#code)
    -   [presentations](#presentations)
  
# Tutorial code
Tutorial Code from PLOS Computation Biology Educational Piece on Efficiency in R. [Download the open access paper](http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004140).

Speeding up ecological and evolutionary computations in R; essentials of high performance computing for biologists.
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## Abstract
Computation has become a critical component of research in biology. A risk has emerged that computational and programming challenges may limit research scope, depth, and quality. We review various solutions to common computational efficiency problems in ecological and evolutionary research. Our review pulls together material that is currently scattered in many sources and emphasizes those techniques that are especially effective for typical ecological and environmental problems. We demonstrate how straightforward it can be to write efficient code and implement techniques such as profiling or parallel computing. We supply a newly developed R-package (aprof) that helps to identify computational bottlenecks in R code and determine whether optimization can be effective. Our review is complemented by a practical set of examples and detailed online material that demonstrate large improvements in computational speed (ranging from 11 to 14 000 times faster). By improving computational efficiency, biologists can feasibly solve more complex tasks, ask more ambitious questions, and include more sophisticated analyses in their research.

## The online code files from S1 Text

Find all code examples from the S1 text in the folder /R or click [here](https://github.com/MarcoDVisser/SpeedUpR/tree/master/R).

## Acknowledgements
As PLOS Computational Biology did not allows us to thank to anonymous reviewers in the above manuscript, I would like to thank them here. Their thoughtful comments and input were very valuable, and resulted in a superiour paper. We wish that PLOS would not take such a stance against gratitute.

# Workshop
Supporting material from the EvoDemos & BES 2015 workshop on code efficiency.

## Code
Find all code exercises [here](https://github.com/MarcoDVisser/SpeedUpR/tree/master/R). 
## Presentations
Presentations with exercies are archived [here](https://github.com/MarcoDVisser/SpeedUpR/tree/master/Workshop).

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