Compositional Data Analysis with Red-R
2011
The compositional analyst must use a series of software to transform raw compositional
data and run statistical analyses on them. Tools for compositional data analysis are
available in R, an open source widely-used statistical computing environment. However,
using R requires prior programming knowledge. Red-R is an open-source, user-friendly
visual data flow interface based on R. The interface uses principles of pipeline
programming where functions are represented as icons, termed widgets, and data flows
from one function to another by drawing lines between them on a canvas. Red-R is able
to perform common data analysis tasks (hypothesis tests, analysis of variance,
regressions, principal component analysis, data cloud plots, bar plots, biplots, etc.). We
have developed a novel Red-R package which implements the compositions package in
R. Our compositions package can be used to perform compositional data operations over
raw data (closure, additive, centered and isometric log ratio transformations,
perturbations and powering, etc.), and create compositional plots (ternary diagrams, ilrdendrograms,
etc.) without prior programming knowledge, after few basic operations.
The objective of this work is to present Red-R and its compositions package using an
application example for geochemical data. The network of widgets provides an easy-tofollow
step-by-step procedure to run a large number of operations available in R, hence
facilitating the tasks of the compositional data analyst. Furthermore, the entire analysis
network can be saved and reloaded. Reports can be generated from the widget network to
document and share results. Non-programmers can have an easy access to the advanced
tools available in compositions analysis
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