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CODAinPractice

COMPOSITIONAL DATA ANALYSIS IN PRACTICE

This repository contains data files and R scripts for the book Compositional Data Analysis in Practice (Michael Greenacre, Chapman & Hall / CRC Press, 2018):

https://www.crcpress.com/Compositional-Data-Analysis-in-Practice/Greenacre/p/book/9781138316430

as well as some other files related to articles on compositional data analysis.


The easyCODA R package accompanies the book and is available on CRAN, presently version 0.34. The package is still under development and the latest version can always be found on R-Forge, installing as follows from R:

install.packages("easyCODA", repos="http://R-Forge.R-project.org")

The package does include the data sets, but the data files are given here as well in Excel or character format.


ERRATA in "Compositional Data Analysis in Practice":

CDAiP_typos.pdf: For the readers of my book, there is a provisional list of errors that I and others have found since its publication.

CDAiP_typos.rtf: rich text format of the above


DATA SETS for Compositional Data Analysis in Practice:

Vegetables.txt: Vegetables data set, data object 'veg' in easyCODA

TimeBudget.txt: Time budget data set, data object 'time' in easyCODA

RomanCups.xls: Archaeometric data on Roman glass cups, data object 'cups' in easyCODA

FishMorphology.txt: Fish morphometric data, with three additional variables, data object 'fish' in easyCODA


R SCRIPTS for Compositional Data Analysis in Practice:

easyCODA_script.R: file of all the R commands in Appendix C, also with some slight corrections.

PLEASE REPORT ANY BUGS OR DIFFICULTIES WITH THE PACKAGE TO Michael Greenacre at michael.greenacre@gmail.com


R scripts and data sets from other publications


ARTICLE: "A comparison of amalgamation logratio balances and isometric logratio balances in compositional data analysis", by Michael Greenacre, Eric Grunsky and John Bacon-Shone, Computers and Geosciences (2020)

CAGEOscript.R: script related Greenacre, Grunsky & Bacon-Shone (2020)


ARTICLE: "Amalgamations are valid in compositional data analysis, can be used in agglomerative clustering, and their logratios have an inverse transformation", by Michael Greenacre, Applied Computing and Geosciences (2020)

SLRscript.R: script related to article


ARTICLE: "The selection and analysis of fatty acid ratios: A new approach for the univariate and multivariate analysis of fatty acid trophic markers in marine pelagic organisms", by Martin Graeve and Michael Greenacre, Limnology & Oceanography Methods (2020)

amphipod_ratios.R: script related to the article by Graeve & Greenacre (2020)

amphipods.csv: data set for R script above

copepod_ratios.R: script related to the article "The selection and analysis of fatty acid ratios: A new approach for the univariate and multivariate analysis of fatty acid trophic markers in marine pelagic organisms", by Martin Graeve and Michael Greenacre, Limnology & Oceanography Methods (2020)

copepods.csv: data set for R script above


ARTICLE: "Compositional Data Analysis", by Michael Greenacre, Annual Reviews in Statistics and its Application (2021)

ANNUALREVIEWSscript.R: R script for article by Greenacre (2021)

copepods_TL.csv: data set for R script above (same data set as for Graeve & Greenacre (2020), with added variable Total Lipids (TL))

Baxter_OTU_table.txt: microbiome data set for R script above. From Baxter et al. (2016)

Baxter_metadata.txt: metadata that goes with the OTU table. From Baxter et al. (2016)


ARTICLE: "Making the most of expert knowledge to analyse archaeologicaldata: a case study on Parthian and Sasanian glazed pottery", by Jonathan Wood and Michael Greenacre, Archaeological and Anthropological Sciences (2021)

Supplementary material for the article by Wood & Greenacre (2021). Two zip files:

Wood&Greenacre_CSV: data files

Wood&Greenacre_CODE&FUNCTIONS: R code and additional R functions


ARTICLE: "Compositional data analysis of microbiome and any-omics datasets: a validation of the additive logratio transformation", by Michael Greenacre, Marina Martinez-Alvaro and Agustin Blasco, Frontiers in Microbiology (2021)

Frontiers_ALR.R: script for Greenacre et al. (2021)

Frontiers_ALR_supplementary.R: script for supplementary material of Greenacre et al. (2021)

FINDALR.R: function FINDALR to identify optimal ALR reference, without or with weights

Rabbits.xlsx: Rabbits data set (89 rows, 3937 columns), rabbits x microbial genes. The different case ID label style refers to the two laboratories that did the testing

Baxter_OTU_table.txt: microbiome data set (Baxter et al., 2016), used in supplementary material of Greenacre et al. (2021)

Baxter_metadata.txt: metadata of above data set (Baxter et al., 2016), used in supplementary material of Greenacre et al. (2021)

Deng_vaginal_microbiome.txt: Vaginal microbiome data (Deng et al., 2018), cited by Wu et al. (2021)


ARTICLE: "Three approaches to supervised learning for compositional data with pairwise logratios", by Germà Coenders and Michael Greenacre (2022)

Coenders&Greenacre_CODE.R: R code for analysis of Crohn data (Crohn data available in R package selbal, as shown in code)

STEPR.R: function for stepwise selection of logratios for GLM models (this function is in the pre-release of easyCODA on RForge)


ARTICLE: "Aitchison's Compositional Data Analysis 40 Years On: A Reappraisal", by Michael Greenacre, Eric Grunsky, John Bacon-Shone, Ionas Erb and Thomas Quinn (2022). There are two versions: the original Version 1, and the new revised Version 2

tellus_Appendix.R: script for reproducing the analysis of the Tellus geochemical data set in Appendix of Version 1

tellus_CoDA_script.R: script for reproducing the analysis of the Tellus geochemical data set in Version 2 (essentially the same as before)

tellus.xrf.a.cation.txt: Tellus cation data set

singlecell_CoDA_script.R: script for reproducing the analysis of the single cell genetic data set in Version 2

SingleCell.RData: R workspace containing all the data files for the single cell application in Section 6 of Version 2


ARTICLE: "GeoCoDA: Recognizing and Validating Structural Processes in Geochemical Data. A Workflow on Compositional Data Analysis in Lithogeochemistry", by Eric Grunsky, Michael Greenacre, and Bruce Kjarsgaard (2023).

kimberlite.cation.txt: kimberlite cation data (Grunsky and Kjarsgaard, 2008)

The distributable R code for this article is in preparation.

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