---
title: "Introduction to the phylocomr package"
author: "Scott Chamberlain and Jeroen Ooms"
date: "`r Sys.Date()`"
output:
  html_document:
    toc: true
    toc_float: true
    theme: readable
vignette: >
  %\VignetteIndexEntry{Introduction to the phylocomr package}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r echo=FALSE}
knitr::opts_chunk$set(
  comment = "#>",
  collapse = TRUE,
  warning = FALSE,
  message = FALSE
)
```

`phylocomr` is an R client for Phylocom - a C library for Analysis of Phylogenetic
Community Structure and Character Evolution.

Phylocom home page is at <http://phylodiversity.net/phylocom/>. The source code
for Phylocom is at <https://github.com/phylocom/phylocom/>.

Phylocom is usually used either on the command line or through the R package
`picante`, which has duplicated some of the Phylocom functionality.

Phylocom has been cited nearly 1000 times according to Google Scholar,
so is clearly a very widely used piece of software. The goal with this package
is to make it even easier to use - and in particular, to incorporate its use into
a reproducible workflow entirely in R instead of going to the shell/command line
for Phylocom usage. (Yes, some of Phylocom functionality is in `picante`, but
not all.)

In terms of performance, some functionality will be faster here than in `picante`,
but the maintainers of `picante` have re-written some Phylocom functionality
in C/C++, so performance should be similar in those cases.

## Install

Install `ape` for below examples:

```{r eval=FALSE}
install.packages('ape')
```

Stable `phylocomr` version from CRAN

```{r eval=FALSE}
install.packages("phylocomr")
```

Or, the development version from Github

```{r eval=FALSE}
devtools::install_github("ropensci/phylocomr")
```

```{r}
library("phylocomr")
```

## phylomatic

```r
taxa_file <- system.file("examples/taxa", package = "phylocomr")
phylo_file <- system.file("examples/phylo", package = "phylocomr")
(taxa_str <- readLines(taxa_file))
(phylo_str <- readLines(phylo_file))
ph_phylomatic(taxa = taxa_str, phylo = phylo_str)
```

## aot

```r
traits_file <- system.file("examples/traits_aot", package = "phylocomr")
phylo_file <- system.file("examples/phylo_aot", package = "phylocomr")
traitsdf_file <- system.file("examples/traits_aot_df", package = "phylocomr")
traits <- read.table(text = readLines(traitsdf_file), header = TRUE,
  stringsAsFactors = FALSE)
phylo_str <- readLines(phylo_file)
ph_aot(traits = traits, phylo = phylo_str)
```

## bladj

```r
ages_file <- system.file("examples/ages", package = "phylocomr")
phylo_file <- system.file("examples/phylo_bladj", package = "phylocomr")
ages_df <- data.frame(
  a = c('malpighiales','salicaceae','fabaceae','rosales','oleaceae',
        'gentianales','apocynaceae','rubiaceae'),
  b = c(81,20,56,76,47,71,18,56)
)
phylo_str <- readLines(phylo_file)
res <- ph_bladj(ages = ages_df, phylo = phylo_str)

if (requireNamespace("ape")) {
  library(ape)
  plot(read.tree(text = res))
}
```

![plot](img/blad_tree.png)
