Skip to content
Back to skills

R Bio Phylo

ASecurity

R phylogenetics with ape, ggtree. Use for phylogenetic trees and evolutionary analysis.

  • 5 stars
  • 0 votes
  • 0 copies
  • 3 views
  • Added June 4, 2026
datagonode

Security analysis

A100/100

Pro scans all 3 files and shows the line behind each finding

Scanned June 4, 2026

npx -y skills add LeoLin990405/r-analytics-skill --skill r-bio-phylo --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of R Bio Phylo?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for R Bio Phylo
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/leolin990405-r-bio-phylo/badge)](https://www.skillsdirectory.com/skills/leolin990405-r-bio-phylo)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: r-bio-phylo
description: R phylogenetics with ape, ggtree. Use for phylogenetic trees and evolutionary analysis.
---

# R Phylogenetics

Phylogenetic analysis and visualization.

## ape

```r
library(ape)

# Read tree
tree <- read.tree("tree.nwk")
tree <- read.nexus("tree.nex")

# Plot
plot(tree)
plot(tree, type = "fan")
plot(tree, type = "cladogram")

# Tree manipulation
drop.tip(tree, c("species1", "species2"))
root(tree, outgroup = "outgroup")
ladderize(tree)

# Distance
cophenetic(tree)
dist.nodes(tree)

# Bootstrap
boot.phylo(tree, data, FUN, B = 100)
```

## ggtree

```r
library(ggtree)

# Basic tree
ggtree(tree) + geom_tiplab()

# Circular
ggtree(tree, layout = "circular") + geom_tiplab()

# With data
ggtree(tree) %<+% metadata +
  geom_tippoint(aes(color = group)) +
  geom_tiplab(aes(label = name))

# Heatmap
gheatmap(ggtree(tree), data, width = 0.3)

# Annotations
ggtree(tree) +
  geom_hilight(node = 10, fill = "blue", alpha = 0.3) +
  geom_cladelabel(node = 10, label = "Clade A")
```

## phangorn

```r
library(phangorn)

# Parsimony
pars <- parsimony(tree, data)
tree_pars <- optim.parsimony(tree, data)

# Maximum likelihood
fit <- pml(tree, data)
fit <- optim.pml(fit, model = "GTR")

# Bootstrap
bs <- bootstrap.pml(fit, bs = 100)
plotBS(tree, bs)
```

Files in this skill

  • SKILL.md1.3 KB
  • ape/SKILL.md3 KB
  • phangorn/SKILL.md1.8 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.