Skip to main content
. 2015 Dec 16;24(8):1195–1201. doi: 10.1038/ejhg.2015.258

Table 1. Comparison of TMRCA methods.

Name Methodology Input classification Input information TMRCA Demographic model
T-LD Statistical estimator from LD Summary statistics of alignments scalable to genomic size LD of variants with genetic distance within 0.005–0.1 cM Point estimation Isolation–migration model
T-FST Statistical estimator from FST and LD Summary statistics of alignments scalable to genomic size LD of variants with genetic distance within 0.005–0.1 cM SNP-wise FST of the two populations Point estimation Isolation–migration model
MIMAR MCMC Summary statistics at multiple neutral loci of size ~1000 bp The summary statistics at each locus: the numbers of polymorphisms unique to the samples from populations 1 and 2; the number of shared alleles between the two samples and the number of fixed alleles in either sample Posterior distribution mean±SD Isolation–migration model or more complex model specified by user
GPho MCMC Full data at multiple neutral loci of size ~1000 bp Each locus provides several samples of diploid or haploid sequences of multiple populations Out-group sequence can be used for mutation rate calibration Posterior distribution mean±SD Phylogeny tree given by user Constant population size to be estimated
DADI Diffusion approximation Summary statistics of alignments scalable to genomic size Allele frequency spectrum of multiple populations Out-group information can be used for polarization Point estimation Demographic function specify by user with sets of parameters to be estimated
CoalHMM HMM–MCMC Full data of alignments scalable to genomic size Two genomic size haploid sequences: one from population_1 and the other one from population_2 Posterior distribution mean±SD Isolation model
PSMC HMM–maximize likelihood estimation Full data of alignments scalable to genomic size Pseudo-diploid sequences constructed from two genomic size haploid sequences: one from population_1 and the other one from population_2 Qualitative estimation. PSMC provides an estimation of historical population size as a step function of time. The time when population size tends to infinity is the divergence time A step function with boundaries of the intervals specified by users and function values to be estimated
MSMC HMM–maximize likelihood estimation Full data of alignments scalable to genomic size Small samples of genomic size phased sequences from two populations. Normally equal numbers of sequences in each of the two populations (2–4 haploid sequences for each population) Qualitative estimation. MSMC provides a metric, relative cross-coalescence rate to measures the gene exchange between two populations. It is a step function of time having value in [0,1]. It shows the dynamic process of relative gene flow changes between two populations, indicating the process of population divergence A step function with boundaries of the intervals specified by users and function values to be estimated