Overview
The cod
R package provides tools for inferring variation in coalescent rates across branches in phylogenetic trees. It provides methods to identify growing lineages, adjust for biased sampling, compute phylogenetic clusters, optimize cluster thresholds, and summarize rate variations.
For worked examples and detailed usage, see package documentation and vigettes at https://emvolz.github.io/cod/.
Installation
You can install cod
from GitHub using devtools
:
# install.packages("devtools")
devtools::install_github("emvolz/cod")
Dependencies
The package requires several dependencies: - Matrix (>= 1.7) - ape (>= 5.0) - glue (>= 1.0.0) - mgcv (>= 1.9-1) - parallel
Optional packages for visualization: - ggtree (>= 3.12.0) - ggplot2 (>= 3.0.0)
Key Features
Estimating Coalescent Odds
The main function codls()
estimates coalescent odds using weighted least squares:
Phylogenetic Clustering
Identify clusters in phylogenetic trees based on coalescent odds:
# Find optimal clustering threshold
chis <- chindices(f, clths = seq(0.1, 1.5, length = 20))
# Compute clusters
clusterdf <- computeclusters(f, clth = chis$threshold[which.max(chis$CH)])
# Plot clusters (requires ggtree)
plotclusters(f, clusterdf)
Adjusting for Sampling Bias
Correct for biased sampling using the sample reweighting method:
# Identify tips to reweight
reweight_tips <- c("tip1", "tip2", "tip3")
# Automatically determine optimal reweighting
reweightedfit <- autoreweight(f, reweight_tips)