phylobar - Interactive construction of stacked barplots using hierarchies

The phylobar package supports interactive visualization of microbiome data by allowing a stacked barplot to be constructed using a guiding taxonomic or phylogenetic hierarchy. The package provides a strategy for collapsing and expanding the hierarchy to different levels of resolution and then for interactively "painting" the stacked barplot by placing the mouse over different subtrees. This makes it possible to interactively test different color palettes at different resolution and identify taxonomic groups with interesting variation before settling on a final stacked barplot. One advantage of the approach is that multiple levels of taxonomic resolution can be compared at once within the same view.

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softwaremicrobiomephylogeneticsvisualization

6.81 score 3 stars

multimedia - Multimodal Mediation Analysis

Multimodal mediation analysis is an emerging problem in microbiome data analysis. Multimedia make advanced mediation analysis techniques easy to use, ensuring that all statistical components are transparent and adaptable to specific problem contexts. The package provides a uniform interface to direct and indirect effect estimation, synthetic null hypothesis testing, bootstrap confidence interval construction, and sensitivity analysis. More details are available in Jiang et al. (2024) "multimedia: Multimodal Mediation Analysis of Microbiome Data" <doi:10.1101/2024.03.27.587024>.

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coveragemicrobiomeregressionsequencingsoftwarestatisticalmethodstructuralequationmodelscausal-inferencedata-integrationmediation-analysis

5.10 score 3 stars 21 scripts 186 downloads

structSSI - Multiple Testing for Hypotheses with Hierarchical or Group Structure

Performs multiple testing corrections that take specific structure of hypotheses into account, as described in Sankaran & Holmes (2014) <doi:10.18637/jss.v059.i13>.

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software

4.83 score 7 stars 24 scripts 272 downloads

miniLNM - Miniature Logistic-Normal Multinomial Models

Logistic-normal Multinomial (LNM) models are common in problems with multivariate count data. This package gives a simple implementation with a 30 line 'Stan' script. This lightweight implementation makes it an easy starting point for other projects, in particular for downstream tasks that require analysis of "compositional" data. It can be applied whenever a multinomial probability parameter is thought to depend linearly on inputs in a transformed, log ratio space. Additional utilities make it easy to inspect, create predictions, and draw samples using the fitted models. More about the LNM can be found in Xia et al. (2013) "A Logistic Normal Multinomial Regression Model for Microbiome Compositional Data Analysis" <doi:10.1111/biom.12079> and Sankaran and Holmes (2023) "Generative Models: An Interdisciplinary Perspective" <doi:10.1146/annurev-statistics-033121-110134>.

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cpp

4.18 score 1 dependents 5 scripts 153 downloads