Markov chain Monte Carlo Gibbs sampler approach for estimating haplotype frequencies among multiple malaria infected human blood samples

Table 2 The similarity index (I_F) of the estimated haplotype frequencies with simulated population and sample haplotype frequencies across statistical methods and four conditions of LoD_SNP (30%, 20%, 10%, 0%) and LoD_MOI (15%, 10%, 5%, 0%)

	MHF	R-EM	Bayesian	EM	MCMC	Gibbs
Population haplotype (LoD_SNP/LoD_MOI)
0/0	0.906	0.879	0.910	0.938	0.915	0.919
0.10/0.05	0.911	0.894	0.913	0.943	0.938	0.934
0.20/0.10	0.905	0.909	0.909	0.940	0.945	0.940
0.30/0.15	0.889	0.918	0.898	0.930	0.930	0.932
Sample haplotype (LoD_SNP/LoD_MOI)
0/0	0.917	0.886	0.917	0.942	0.917	0.921
0.10/0.05	0.923	0.904	0.922	0.950	0.942	0.939
0.20/0.10	0.915	0.920	0.917	0.948	0.953	0.948
0.30/0.15	0.897	0.930	0.906	0.938	0.937	0.942

Higher value represents higher accuracy
MHF MalHaploFreq, R-EM malaria em, Bayesian Bayesian statistic, EM EM algorithm, MCMC Markov chain Monte Carlo, Gibbs Gibbs sampler, LoD limit of detection, SNP single nucleotide polymorphisms, MOI multiplicity of infection

ISSN: 1475-2875