Welcome to the balance
GitHub page!
Balances have become a cornerstone of compositional data analysis. However, conceptualizing balances is difficult, especially for high-dimensional data. Most often, investigators visualize balances with "balance dendrograms". However, this visualization tool does not scale well for large data. This package provides an alternative scheme for visualizing balances.
library(devtools)
devtools::install_github("tpq/balance")
library(balance)
?balance
We will demonstrate this package using an example from the robCompositions
package. The "expenditures" matrix contains 20 compositions (row), each measuring 5 components (columns). As compositional data, the abundances are irrelevant and each composition sums to unity. The "y1" matrix is a serial binary partition (SBP) matrix that describes how to partition the 5 components into 4 balances.
data(expenditures, package = "robCompositions")
y1 <- data.frame(c(1, 1, 1, -1, -1), c(1, -1, -1, 0, 0),
c(0, +1, -1, 0, 0), c(0, 0, 0, +1, -1))
colnames(y1) <- paste0("z", 1:4)
With the data loaded, we can calculate and visualize the balances.
res <- balance.plot(expenditures, y1, size.text = 8)
Optionally, users can color components (in left figure) or samples (in right figure) based on a user-defined grouping. To do this, users must provide a vector of group labels for each component via the d.group
argument (or for each sample via the n.group
argument). Here, we color components and samples by user-defined groupings.
res <- balance.plot(expenditures, y1,
d.group = c("A", "B", "A", "B", "C"),
n.group = c(rep("A", 10), rep("B", 10)),
size.text = 8)
To learn more about balance
, please see the vignette and relevant literature.
citation("balance")
#>
#> To cite balance in publications use:
#>
#> Quinn T. 2018. Visualizing balances of compositional data: A new
#> alternative to balance dendrograms. F1000Research, 7:1278. URL
#> https://f1000research.com/articles/7-1278.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Article{,
#> title = {Visualizing balances of compositional data: A new alternative to balance dendrograms},
#> author = {Thomas Quinn},
#> journal = {F1000Research},
#> year = {2018},
#> volume = {7},
#> number = {1278},
#> url = {https://f1000research.com/articles/7-1278},
#> }