Skip to content
diversity estimation under ecological networks
Branch: master
Clone or download
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
R Merge pull request #20 from adw96/testing Dec 6, 2018
data add Lee data; new vignette; phyloseq integration Apr 18, 2018
docs Update logo Aug 3, 2018
inst/doc
man Fix OLS with X = 0 covariates. Fixes #9 Dec 6, 2018
tests Define n in test_correct Jan 12, 2019
vignettes new vignettes for testing Aug 22, 2018
.Rbuildignore try appveyor May 28, 2018
.gitattributes try appveyor May 28, 2018
.gitignore try appveyor May 28, 2018
.travis.yml Need newer breakaway Jul 28, 2018
DESCRIPTION Merge pull request #20 from adw96/testing Dec 6, 2018
NAMESPACE man and NAMESPACE for simplifyBeta Aug 1, 2018
README.Rmd Update logo Aug 3, 2018
README.md Update logo Aug 3, 2018
appveyor.yml try appveyor May 28, 2018
divnet-build-and-test.R beta diversity utility Aug 1, 2018

README.md


DivNet

Build Status codecov.io

DivNet: an R package to estimate diversity when taxa in the community cooccur via a ecological network.

Willis, A.D. and Martin, B.D. (2018+) DivNet: Estimating diversity in networked communities. Under review.

About

If you new the exact composition of a community (such as all of the microbes living on your skin), you could calculate the Shannon diversity of the community, or the Bray-Curtis distance between your skin's microbes and your cat's fur microbes. However, you will only ever observe a small fraction of the microbes on your skin from your experiment, so you have to estimate these diversity indices based on the data, and ideally you will get a confidence interval for those diversity indices.

Almost all ecologists use "plug-in" diversity estimates, obtained by taking the observed relative abundances of each taxon and plugging them into the formula for the true diversity. This is problematic for a number of reasons, including that there may be unobserved taxa, and the observed relative abundances probably don't exactly equal the true relative abundances due to random sampling. Furthermore, typical approaches to obtaining a confidence interval assume that all taxa behave independently: if taxon A is there, this tells you nothing about whether taxon B is likely to be there too. DivNet takes care of all of these issues, and gives you a confidence interval that incorporates all of these challenges.

See here for a full tutorial, and the paper for more details.

Want a confidence interval for a different diversity index? Let us know by posting an issue!

Installation

library(devtools)
install_github("adw96/DivNet")
library(DivNet)

Basic Usage

Let's analyse the Lee et al. dataset using DivNet. We could analyse at the ASV level, but to keep things simple let's analyse the phylum level diversity.

library(phyloseq)
data(Lee)
divnet_phylum <-  divnet(tax_glom(Lee, taxrank="Phylum"),
                         X = "char",
                         ncores = 4)
divnet_phylum

To test if alpha-diversity (by default, Shannon) is equal across the values of the covariate X, we can run

testDiversity(divnet_phylum)

and to plot the DivNet estimates of diversity we can run

library(ggplot2)
plot(divnet_phylum)

Integration

DivNet integrates with - phyloseq (for reproducible microbiome analysis) - breakaway (for hypothesis testing)

Coming soon

  • DivNet will hopefully soon be available as a QIIME2 plug-in
  • The same philosophy of DivNet can be applied to estimating UniFrac and other diversity indices that are a function of phylogeny. Watch this space!
You can’t perform that action at this time.