The apps in this directory will allow you to perform a set of statistical analysis and screens typically suited to ecological data sets. These accompany an online guide to statistical analysis in microbial ecology, available here: http://mb3is.megx.net/gustame
Please see the following publication for more: Buttigieg PL, Ramette A (2014) A Guide to Statistical Analysis in Microbial Ecology: a community-focused, living review of multivariate data analyses. FEMS Microbiol Ecol. 90: 543–550. http://dx.doi.org/10.1111/1574-6941.12437
If you have queries, wish to report errors, or have enhancement requests, contact Pier Luigi Buttigieg.
If you'd like to fork the code to improve or extend it, we're more than happy to integrate pull requests here and in GUSTA ME. It would be even better if you have knowledge to share via GUSTA ME itself! Of course, all contributions will be micro-credited.
You can run any of these apps on your own machine (assuming you've cloned the code locally and have all the R packages you need) by using the runApp() function from shiny. These are at the top of most scripts in this repo. For example, to run the ANOSIM app on your computer from the top level directory ("masame"), type the following in your R console:
runApp('./ANOSIM', launch.browser = TRUE) To launch an analysis app online, please click the link to the corresponding GUSTA ME page below and scroll to the bottom where the a launch link will be provided.
- screen your data set for multicollinear variables using correlation-based approaches
- screen your data set for univariate and multivariate normality and apply transformations
- screen your data set for univariate and multivariate outliers
- Principal components analysis
- (partial) redundancy analysis
- distance-based redundancy analysis
- (partial) canonical correspondence analysis
- Metric multidimensional scaling analysis or principal coordinates analysis
- Hierarchical cluster analysis
- Non-metric multidimensional scaling analysis
- Principal coordinates of neighbour matrices analysis
Please find demo data sets in the "Example data sets" directory. These are correctly formatted for upload to MASAME Apps under the default upload settings. More information is available in the README file in the directory.
Some apps have been updated to support colour-coding, vegan's ordination hulls, spiders, and ellipses, and more transformations.
If you'd like to try them out, they're in the experimentalUpdates folder. You'll have to run them locally (see below for brief instructions), but it's quite straightforward to do so.