From hairballs to hypotheses–biological insights from microbial networks
L Röttjers, K Faust - FEMS microbiology reviews, 2018 - academic.oup.com
Microbial networks are an increasingly popular tool to investigate microbial community
structure, as they integrate multiple types of information and may represent systems-level …
structure, as they integrate multiple types of information and may represent systems-level …
Integrating sleep, sedentary behaviour, and physical activity research in the emerging field of time-use epidemiology: definitions, concepts, statistical methods …
INTEGRATING SLEEP, SEDENTARY BEHAVIOUR, AND PHYSICAL ACTIVITY
RESEARCH IN THE EMERGING FIELD OF TIME-USE EPIDEMIOLOGY: DEFINITIO Page 1 …
RESEARCH IN THE EMERGING FIELD OF TIME-USE EPIDEMIOLOGY: DEFINITIO Page 1 …
zCompositions—R package for multivariate imputation of left-censored data under a compositional approach
J Palarea-Albaladejo, JA Martín-Fernández - Chemometrics and Intelligent …, 2015 - Elsevier
Abstract zCompositions is an R package for the imputation of left-censored data under a
compositional approach. It is pertinent when the analyst assumes that the relevant …
compositional approach. It is pertinent when the analyst assumes that the relevant …
Compositional data analysis of the microbiome: fundamentals, tools, and challenges
MCB Tsilimigras, AA Fodor - Annals of epidemiology, 2016 - Elsevier
Purpose Human microbiome studies are within the realm of compositional data with the
absolute abundances of microbes not recoverable from sequence data alone. In …
absolute abundances of microbes not recoverable from sequence data alone. In …
Compositional data analysis of microbiome and any-omics datasets: a validation of the additive logratio transformation
Microbiome and omics datasets are, by their intrinsic biological nature, of high
dimensionality, characterized by counts of large numbers of components (microbial genes …
dimensionality, characterized by counts of large numbers of components (microbial genes …
Bayesian-multiplicative treatment of count zeros in compositional data sets
JA Martín-Fernández, K Hron, M Templ… - Statistical …, 2015 - journals.sagepub.com
Compositional count data are discrete vectors representing the numbers of outcomes falling
into any of several mutually exclusive categories. Compositional techniques based on the …
into any of several mutually exclusive categories. Compositional techniques based on the …
[HTML][HTML] Comparison of zero replacement strategies for compositional data with large numbers of zeros
Modern applications in chemometrics and bioinformatics result in compositional data sets
with a high proportion of zeros. An example are microbiome data, where zeros refer to …
with a high proportion of zeros. An example are microbiome data, where zeros refer to …
Compositional data analysis
M Greenacre - Annual Review of Statistics and its Application, 2021 - annualreviews.org
Compositional data are nonnegative data carrying relative, rather than absolute, information—
these are often data with a constant-sum constraint on the sample values, for example …
these are often data with a constant-sum constraint on the sample values, for example …
coda4microbiome: compositional data analysis for microbiome cross-sectional and longitudinal studies
Background One of the main challenges of microbiome analysis is its compositional nature
that if ignored can lead to spurious results. Addressing the compositional structure of …
that if ignored can lead to spurious results. Addressing the compositional structure of …
Compositional data: the sample space and its structure
JJ Egozcue, V Pawlowsky-Glahn - Test, 2019 - Springer
The log-ratio approach to compositional data (CoDa) analysis has now entered a mature
phase. The principles and statistical tools introduced by J. Aitchison in the eighties have …
phase. The principles and statistical tools introduced by J. Aitchison in the eighties have …