R-universe search: topic:phyloseq

Showing 5 of total 5 results (show query)

bioc

microbiome:Microbiome Analytics

Utilities for microbiome analysis.

Maintained by Leo Lahti. Last updated 5 months ago.

metagenomics microbiome sequencing systemsbiology hitchip hitchip-atlas human-microbiome microbiology microbiome-analysis phyloseq population-study

293 stars 12.51 score 2.0k scripts 5 dependents

bioc

RCM:Fit row-column association models with the negative binomial distribution for the microbiome

Combine ideas of log-linear analysis of contingency table, flexible response function estimation and empirical Bayes dispersion estimation for explorative visualization of microbiome datasets. The package includes unconstrained as well as constrained analysis. In addition, diagnostic plot to detect lack of fit are available.

Maintained by Stijn Hawinkel. Last updated 5 months ago.

metagenomics dimensionreduction microbiome visualization ordination phyloseq rcm

16 stars 6.90 score 25 scripts

bioc

dar:Differential Abundance Analysis by Consensus

Differential abundance testing in microbiome data challenges both parametric and non-parametric statistical methods, due to its sparsity, high variability and compositional nature. Microbiome-specific statistical methods often assume classical distribution models or take into account compositional specifics. These produce results that range within the specificity vs sensitivity space in such a way that type I and type II error that are difficult to ascertain in real microbiome data when a single method is used. Recently, a consensus approach based on multiple differential abundance (DA) methods was recently suggested in order to increase robustness. With dar, you can use dplyr-like pipeable sequences of DA methods and then apply different consensus strategies. In this way we can obtain more reliable results in a fast, consistent and reproducible way.

Maintained by Francesc Catala-Moll. Last updated 17 days ago.

software sequencing microbiome metagenomics multiplecomparison normalization bioconductor biomarker-discovery differential-abundance-analysis feature-selection microbiology phyloseq

2 stars 5.98 score 8 scripts

bewicklab

holobiont:Microbiome Analysis Tools

We provide functions for identifying the core community phylogeny in any microbiome, drawing phylogenetic Venn diagrams, calculating the core Faith’s PD for a set of communities, and calculating the core UniFrac distance between two sets of communities. All functions rely on construction of a core community phylogeny, which is a phylogeny where branches are defined based on their presence in multiple samples from a single type of habitat. Our package provides two options for constructing the core community phylogeny, a tip-based approach, where the core community phylogeny is identified based on incidence of leaf nodes and a branch-based approach, where the core community phylogeny is identified based on incidence of individual branches. We suggest use of the microViz package, which can be downloaded from the website provided under Additional repositories.

Maintained by Sharon Bewick. Last updated 6 months ago.

software phyloseq

1.00 score

bewicklab

HybridMicrobiomes:Analysis of Host-Associated Microbiomes from Hybrid Organisms

A set of tools to analyze and visualize the relationships between host-associated microbiomes of hybrid organisms and those of their progenitor species. Though not necessary, installing the microViz package is recommended as a check for phyloseq objects. To install microViz from R Universe use the following command: install.packages("microViz", repos = c(davidbarnett = "https://david-barnett.r-universe.dev", getOption("repos"))). To install microViz from GitHub use the following commands: install.packages("devtools") followed by devtools::install_github("david-barnett/microViz").

Maintained by Sharon Bewick. Last updated 1 years ago.

software phyloseq

1.00 score