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

Table 5 Percentages of simulated sample haplotype frequencies and population haplotype frequencies that fall outside the confidence intervals of the estimated 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	4.90	5.90	14.60	0.70	4.00	3.00
0.10/0.05	6.20	5.70	15.10	1.00	1.30	1.90
0.20/0.10	11.40	5.90	18.10	2.00	1.80	2.10
0.30/0.15	20.00	8.10	23.30	4.30	4.40	3.80
Sample haplotype (LoD_SNP/LoD_MOI)
0/0	6.90	8.30	14.80	4.50	8.00	6.40
0.10/0.05	7.50	7.50	14.50	4.40	5.10	4.80
0.20/0.10	11.50	6.80	17.10	4.40	4.40	4.60
0.30/0.15	20.30	8.20	21.60	5.40	5.40	5.20

Lower 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