Historical (Ancient) Samples

Sometimes you may wish to infer and date a genetic genealogy from data which includes historical samples, whose time is older that the current generation (i.e. sample nodes with times > 0).

The output of tsinfer is valid regardless of the inclusion of historical samples, but dating such a tree sequence is more complicated. This is because the time scale of a tsinferred tree sequence is uncalibrated, so it is unclear where in time to place any historical samples.

Note

We are currently working on methods to make dating historical samples much more convenient.

The 2 step approach

Currently, the best way to date such tree sequences is to perform a two step process, in which inference and dating is first performed on the modern samples in order to establish a timescale, followed by adding the historical samples and re-inferring using the dated timescale as a basis for site ages in the tsinfer algorithm. The re-inferred tree sequence can then be redated. The following recipe shows how this is accomplished with a few lines of Python. The only requirement is a tsinfer.SampleData file with modern and historical samples (the latter are specified using the individuals_time array in a tsinfer.SampleData file).

Note

While tsinfer does not make assumptions about the time of sample nodes, tsdate requires a prior which is calculated from the conditional coalescent on the assumption that all samples are at time 0. Although this is not the case if there are historical samples, testing shows that it is still a close enough approximation for the method to work well.

import logging

import msprime
import tsinfer
import tsdate

Ne = 1e4
mu = 1e-7  # mutation rate

def make_historical_data(num_modern, num_historical, random_seed, historical_time = 10000):
    # Returns two SampleData files, one with only moderns and one with everyone
    samples = [
        msprime.SampleSet(num_modern),
        msprime.SampleSet(num_historical, time=historical_time)
    ]
    
    ts = msprime.sim_ancestry(
        samples=samples,
        population_size=Ne,
        recombination_rate=1e-7, 
        sequence_length=1e5,
        random_seed=random_seed
    )
    ts = msprime.sim_mutations(ts, rate=mu, random_seed=random_seed)
    ## Make the SampleData files directly from the tree sequence rather than going via VCF
    all_samples = tsinfer.SampleData.from_tree_sequence(
        ts, use_sites_time=True, use_individuals_time=True)
    modern_samples = tsinfer.SampleData.from_tree_sequence(
        ts.simplify(ts.samples(time=0), filter_sites=False))

    # NB: if importing from a VCF you would create the modern_samples by subsetting all_samples:
    # modern_samples = all_samples.subset(np.where(all_samples.individuals_time[:] == 0)[0])
    return modern_samples, all_samples

def infer_and_date_modern_and_ancient(modern_samples, all_samples):
    # Date the moderns
    inferred_ts = tsinfer.infer(modern_samples)

    tsdate_logger = logging.getLogger('tsdate')  # temporarily disable the warning
    tsdate_logger.setLevel(logging.CRITICAL)
    inferred_ts = tsdate.preprocess_ts(inferred_ts)
    tsdate_logger.setLevel(logging.WARNING)

    dated_modern_ts = tsdate.date(inferred_ts,  mutation_rate=mu)
    
    # Find the dates for each site and use those rather than frequency
    sites_time = tsdate.sites_time_from_ts(dated_modern_ts)  # Get tsdate site age estimates
    dated_samples = tsdate.add_sampledata_times(all_samples, sites_time)
    ancestors = tsinfer.generate_ancestors(dated_samples)
    ancestors_w_proxy = ancestors.insert_proxy_samples(
        dated_samples, allow_mutation=True)
    ancestors_ts = tsinfer.match_ancestors(dated_samples, ancestors_w_proxy)
    return tsinfer.match_samples(dated_samples, ancestors_ts, force_sample_times=True)

dated_ts = infer_and_date_modern_and_ancient(*make_historical_data(2, 1, random_seed=1234))

In the code above, we simulate a tree sequence with six sample chromosomes, four modern and two historical. We then infer and date a tree sequence using only the modern samples. Next, we find derived alleles which are carried by the historical samples and use the age of the historical samples to constrain the ages of these alleles. Finally, we reinfer the tree sequence, using the date estimates from tsdate and the historical constraints rather than the frequency of the alleles to order mutations in tsinfer. Historical samples are added to the ancestors tree sequence as proxy nodes, in addition to being used as samples.