phylo_info.Rmd

---
title: "summary_data"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
```


```{r}
library(geiger)

tr  <- read.tree("/home/blubb/Documents/Workshops_PD/Ithaca_2018/example_data_ARBOR/CostaRicaHeliconia.tre.phy")
```

## Phylogenetic information

loaded phylogeny:

```{r, echo = FALSE}
plot(tr, cex = 0.5)
```

```{r, echo = FALSE}

ultra <- function(tr){
  if (ape::is.ultrametric(tr) == TRUE){
     return("ultrametric")
  }else{
     return("not ultrametric")
  }
}
# is it ultrametric

```

The phylogeny includes `r tr$Nnode` nodes and is `r ultra(tr)`.

## Compare lineage to OpenTreeOfLife

```{r}
library(rotl)
name = "Heliconia"
```



```{r}
resolved_names <- tnrs_match_names(name)
id <- ott_id(resolved_names)
tr_otol <- tol_subtree(ott_id = id[[1]])
sampling = (tr$Nnode) / (tr_otol$Nnode)
hierarchy = tax_lineage(taxonomy_taxon_info(id, include_lineage = TRUE))

```

You are comparing `r resolved_names$unique_name` to OpenTree, which has the ott `r id[[1]]` .

Here are the corresponding rank information to your group:
```{r}
print(hierarchy)
```

The phylogeny from OToL looks like this and has `r tr_otol$Nnode` nodes: 
```{r}
plot(tr_otol)
```

Compared to that, your sampling proportion is `r sampling`.