Version Compatibility

Reference examples tested with: BioPython 1.83+, TreeTime 0.11+, matplotlib 3.8+, numpy 1.26+, pandas 2.2+, scanpy 1.10+

Before using code patterns, verify installed versions match. If versions differ:

• Python: pip show <package> then help(module.function) to check signatures
• R: packageVersion('<pkg>') then ?function_name to verify parameters

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Transmission Inference

"Infer who infected whom in my outbreak" → Reconstruct transmission networks from genomic and epidemiological data to identify transmission pairs, superspreaders, and unsampled cases.

• R: TransPhylo::inferTTree() for Bayesian transmission tree inference

TransPhylo in R

library(TransPhylo)
library(ape)

# Load dated phylogeny (from BEAST/TreeTime)
tree <- read.nexus('dated_tree.nexus')

# Convert to TransPhylo format
ptree <- ptreeFromPhylo(tree, dateLastSample = 2020.5)

# Estimate transmission tree
# Uses MCMC to sample from posterior distribution
res <- inferTTree(
    ptree,
    mcmcIterations = 100000,
    startNeg = 0.1,      # Initial within-host effective population
    startOff.r = 2,      # Initial R0 estimate
    startOff.p = 0.5,    # Initial sampling probability
    startPi = 0.9,       # Initial probability of being sampled
    dateT = 2020.6       # End of outbreak observation
)

# Extract consensus transmission tree
ttree <- extractTTree(res)

# Get transmission pairs
pairs <- ttree$ttree[, c('infector', 'infectee', 'time')]

Prepare Data

def prepare_for_transphylo(dated_tree_file, sample_dates, output_prefix):
    '''Prepare inputs for TransPhylo analysis

    Requirements:
    - Time-scaled phylogeny (from TreeTime or BEAST)
    - Sample collection dates
    - Tips must have matching names

    TransPhylo estimates:
    - Who infected whom
    - Unsampled cases in the transmission chain
    - R0 and generation time
    '''
    from Bio import Phylo
    import pandas as pd

    tree = Phylo.read(dated_tree_file, 'nexus')

    # Verify all tips have dates
    dates_df = pd.read_csv(sample_dates, sep='\t')
    tip_names = {clade.name for clade in tree.get_terminals()}
    dated_names = set(dates_df['name'])

    missing = tip_names - dated_names
    if missing:
        print(f'Warning: {len(missing)} tips without dates: {missing}')

    return {'tree': dated_tree_file, 'dates': sample_dates}