-
Notifications
You must be signed in to change notification settings - Fork 0
/
README.Rmd
126 lines (90 loc) · 4.86 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
---
output: github_document
bibliography: vignettes/bibliography.bib
nocite: '@*'
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = NULL
)
Sys.setlocale("LC_MESSAGES", 'en_GB.UTF-8') # Force locale
```
# nexus <img width=120px src="man/figures/logo.png" align="right" />
<!-- badges: start -->
[](https://github.com/tesselle/nexus/actions)
[](https://app.codecov.io/gh/tesselle/nexus)
[](https://www.codefactor.io/repository/github/tesselle/nexus/overview/main)
[](https://cran.r-project.org/package=nexus)
[](https://tesselle.r-universe.dev/nexus){.pkgdown-devel}
[](https://cran.r-project.org/package=nexus){.pkgdown-release}
[](https://cran.r-project.org/web/checks/check_results_nexus.html){.pkgdown-release}
[](https://cran.r-project.org/package=nexus){.pkgdown-release}
[](https://www.repostatus.org/#wip)
[](https://doi.org/10.5281/zenodo.10225630)
<!-- badges: end -->
## Overview
This package is currently *experimental*. This means that it is functional, but interfaces and functionalities may change over time, testing and documentation may be lacking.
Exploration and analysis of compositional data in the framework of @aitchison1986. **nexus** provides tools for chemical fingerprinting and source tracking of ancient materials. This package provides methods for compositional data analysis:
* Compositional statistics.
* Compositional data visualization.
* Logratio transformations: `transform_lr()`, `transform_clr()`, `transform_alr()`, `transform_ilr()`, `transform_plr()`.
* Zero and missing value replacement.
* Outlier detection: `detect_outlier()`.
This package also includes methods for provenance studies:
* Multivariate analysis: `pca()`.
* Mixed-mode analysis using geochemical and petrographic data [@baxter2008]: `mix()`.
[**isopleuros**](https://packages.tesselle.org/isopleuros/) is a companion package to **nexus** that allows to create ternary plots.
---
```{r citation, echo=FALSE, comment='', results='asis'}
cite <- utils::citation("nexus")
print(cite, bibtex = FALSE)
```
## Installation
You can install the released version of **nexus** from [CRAN](https://CRAN.R-project.org) with:
```{r cran-installation, eval=FALSE}
install.packages("nexus")
```
And the development version from [GitHub](https://github.com/) with:
```{r gh-installation, eval=FALSE}
# install.packages("remotes")
remotes::install_github("tesselle/nexus")
```
## Usage
```{r packages}
## Install extra packages (if needed)
# install.packages("folio")
## Load the package
library(nexus)
```
**nexus** provides a set of S4 classes that represent different special types of matrix (see `vignette("nexus")`). The most basic class represents a compositional data matrix, i.e. quantitative (nonnegative) descriptions of the parts of some whole, carrying relative, rather than absolute, information [@aitchison1986].
*It assumes that you keep your data tidy*: each variable must be saved in its own column and each observation (sample) must be saved in its own row.
```{r groups}
## Data from Wood and Liu 2023
data("bronze", package = "folio")
## Coerce to compositional data
coda <- as_composition(bronze, parts = 4:11)
## Use dynasties as groups
groups(coda) <- bronze$dynasty
```
```{r barplot, fig.width=5, fig.height=7}
## Compositional barplots of major elements
barplot(coda, select = is_element_major(coda), order_rows = "Cu",
border = NA, space = 0)
```
```{r lra, fig.width=7, fig.height=7, out.width='50%', fig.show='hold'}
## Log-ratio analysis
## (PCA of centered log-ratio; outliers should be removed first)
clr <- transform_clr(coda, weights = TRUE)
lra <- pca(clr)
## Visualize results
viz_individuals(lra, color = c("#004488", "#DDAA33", "#BB5566"))
viz_hull(x = lra, border = c("#004488", "#DDAA33", "#BB5566"))
viz_variables(lra)
```
## Contributing
Please note that the **nexus** project is released with a [Contributor Code of Conduct](https://www.tesselle.org/conduct.html). By contributing to this project, you agree to abide by its terms.
## References