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https://github.com/daijiang/phyr

Functions for phylogenetic analyses
https://github.com/daijiang/phyr

bayesian glmm inla phylogeny r rpackage species-distribution-modeling

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Functions for phylogenetic analyses

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README 

        
---

output: github_document

---



```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "##",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```



# phyr 



[![R-CMD-check](https://github.com/daijiang/phyr/workflows/R-CMD-check/badge.svg)](https://github.com/daijiang/phyr/actions)

[![Codecov test coverage](https://codecov.io/gh/daijiang/phyr/branch/master/graph/badge.svg)](https://app.codecov.io/gh/daijiang/phyr?branch=master)



# Installation



To install this package:



```{r eval = F}

options(repos = c(

  phyr = 'https://daijiang.r-universe.dev',

  CRAN = 'https://cloud.r-project.org'))

install.packages('phyr')



# or

devtools::install_github("daijiang/phyr")

```



# Main functions



The phyr package has three groups of functions:



1. community phylogenetic diversity metrics (alpha: `psv`, `psr`, `pse`, etc. and beta: `pcd`), which were included in the `picante` package originally. They were updated with c++ to improve speed.

2. models to estimate correlation between functional traits while accounting for phylogenetic relationships (`cor_phylo`), which was included in the `ape` package originally. It has new syntax, much improved performance (c++), and bootstrapping option.

3. phylogenetic generalized linear mixed models (`pglmm`), which was originally included in the `pez` package. It has new model formula syntax that allows straightforward model set up, a faster version of maximum likelihood implementation via c++, and a Bayesian model fitting framework based on INLA. 

    + We hope the model formula proposed here can be used to standardize PGLMMs set up across different tools (e.g. `brms` for Stan).

    + PGLMM for comparative data (`pglmm.compare`), which was originally from `ape::binaryPGLMM()` but has more features.



# Usage examples of `pglmm()`



`pglmm` use similar syntax as `lme4::lmer` to specify random terms: add `__` (two underscores) at the end of grouping variable (e.g. `sp`) to specify both phylogenetic and non-phylogenetic random terms; use `(1|sp__@site)` to specify nested term (i.e. species phylogenetic matrix `V_sp` nested within the diagonal of site matrix `I_site`) to test phylogenetic overdispersion or underdispersion. This should be the most commonly used one and is equal to `kronecker(I_site, V_sp)`. 



We can also use a second phylogeny for bipartite questions. For example, `(1|parasite@host__)` will be converted to `kronecker(V_host, I_parasite)`; `(1|parasite__@host__)` will be converted to `kronecker(V_host, V_parasite)`.



For details about model formula, see documentation `?phyr::pglmm`. More application examples can be found in [Ives 2018 Chapter 4](https://leanpub.com/correlateddata).



```{r message=FALSE}

library(phyr)

```



```{r eval = T}

library(dplyr)

comm = comm_a

comm$site = row.names(comm)

dat = tidyr::gather(comm, key = "sp", value = "freq", -site) %>% 

  left_join(envi, by = "site") %>% 

  left_join(traits, by = "sp")

dat$pa = as.numeric(dat$freq > 0)

head(dat)

# phy-LMM

test1 = phyr::pglmm(freq ~ 1 + shade + (1|sp__) + (1|site) + (1|sp__@site), 

                    data = dat, family = "gaussian", REML = FALSE,

                    cov_ranef = list(sp = phylotree))

test1

# phy-GLMM

test2 = phyr::pglmm(pa ~ 1 + shade + (1|sp__) + (1|site) + (1|sp__@site), 

                    data = dat, family = "binomial", REML = FALSE,

                    cov_ranef = list(sp = phylotree))

test2

# bipartite

tree_site = ape::rtree(n = n_distinct(dat$site), tip.label = sort(unique(dat$site)))

z_bipartite = phyr::pglmm(freq ~ 1 + shade + (1|sp__) + (1|site__) + 

                            (1|sp__@site) + (1|sp@site__) + (1|sp__@site__), 

                          data = dat, family = "gaussian",REML = TRUE,

                          cov_ranef = list(sp = phylotree, site = tree_site))

z_bipartite

```



# Licenses



Licensed under the [GPL-3 license](https://www.gnu.org/licenses/gpl-3.0.en.html).



# Contributing



Contributions are welcome. You can provide comments and feedback or ask questions by filing an issue on Github [here](https://github.com/daijiang/phyr/issues) or making pull requests.



# Code of conduct



Please note that the 'phyr' project is released with a [Contributor Code of Conduct](https://github.com/daijiang/phyr/blob/master/CODE_OF_CONDUCT.md). By contributing to this project, you agree to abide by its terms.