scholarly journals Haplotype inference for present–absent genotype data using previously identified haplotypes and haplotype patterns

2007 ◽  
Vol 23 (18) ◽  
pp. 2399-2406 ◽  
Author(s):  
Yun Joo Yoo ◽  
Jianming Tang ◽  
Richard A. Kaslow ◽  
Kui Zhang
Keyword(s):  
Haplotype Inference ◽  
Genotype Data

A fast haplotype inference method for large population genotype data

2008 ◽  
Vol 52 (11) ◽  
pp. 4891-4902 ◽  
Author(s):  
Ji-Hong Zhang ◽  
Ling-Yun Wu ◽  
Jian Chen ◽  
Xiang-Sun Zhang
Keyword(s):  
Large Population ◽  
Haplotype Inference ◽  
Genotype Data ◽  
Inference Method

scholarly journals HAPLOTYPE INFERENCE WITH BOOLEAN SATISFIABILITY

2008 ◽  
Vol 17 (02) ◽  
pp. 355-387 ◽  
Author(s):  
INÊS LYNCE ◽  
JOÃO MARQUES-SILVA
Keyword(s):  
Human Population ◽  
Haplotype Inference ◽  
Genotype Data ◽  
Nucleotide Polymorphisms ◽  
Human Beings ◽  
Single Nucleotide ◽  
Haplotype Data ◽  
Np Hard Problem ◽  
Pure Parsimony ◽  
Parsimony Criterion

Mutation in DNA is the principal cause for differences among human beings, and Single Nucleotide Polymorphisms (SNPs) are the most common mutations. Hence, a fundamental task is to complete a map of haplotypes (which identify SNPs) in the human population. Associated with this effort, a key computational problem is the inference of haplotype data from genotype data, since in practice genotype data rather than haplotype data is usually obtained. Different haplotype inference approaches have been proposed, including the utilization of statistical methods and the utilization of the pure parsimony criterion. The problem of haplotype inference by pure parsimony (HIPP) is interesting not only because of its application to haplotype inference, but also because it is a challenging NP-hard problem, being APX-hard. Recent work has shown that a SAT-based approach is the most efficient approach for the problem of haplotype inference by pure parsimony (HIPP), being several orders of magnitude faster than existing integer linear programming and branch and bound solutions. This paper provides a detailed description of SHIPs, a SAT-based approach for the HIPP problem, and presents comprehensive experimental results comparing SHIPs with all other exact approaches for the HIPP problem. These results confirm that SHIPs is currently the most effective approach for the HIPP problem.

Analysis of Flavin-Containing Monooxygenase 3 Genotype Data in Populations Administered the Anti-Schizophrenia Agent Olanzapine

2008 ◽  
Vol 2 (2) ◽  
pp. 100-114 ◽  
Author(s):  
John Cashman ◽  
Jun Zhang ◽  
Matthew Nelson ◽  
Andreas Braun
Keyword(s):  
Genotype Data

Bayesian Inference of Recent Migration Rates Using Multilocus Genotypes

Genetics ◽  
2003 ◽  
Vol 163 (3) ◽  
pp. 1177-1191 ◽  
Author(s):  
Gregory A Wilson ◽  
Bruce Rannala
Keyword(s):  
Probability Distributions ◽  
Gray Wolf ◽  
Data Sets ◽  
Genotype Data ◽  
Migration Rates ◽  
Multilocus Genotypes ◽  
Monte Carlo Techniques ◽  
Inbreeding Coefficients ◽  
Genotype Frequencies ◽  
Marker Loci

Abstract A new Bayesian method that uses individual multilocus genotypes to estimate rates of recent immigration (over the last several generations) among populations is presented. The method also estimates the posterior probability distributions of individual immigrant ancestries, population allele frequencies, population inbreeding coefficients, and other parameters of potential interest. The method is implemented in a computer program that relies on Markov chain Monte Carlo techniques to carry out the estimation of posterior probabilities. The program can be used with allozyme, microsatellite, RFLP, SNP, and other kinds of genotype data. We relax several assumptions of early methods for detecting recent immigrants, using genotype data; most significantly, we allow genotype frequencies to deviate from Hardy-Weinberg equilibrium proportions within populations. The program is demonstrated by applying it to two recently published microsatellite data sets for populations of the plant species Centaurea corymbosa and the gray wolf species Canis lupus. A computer simulation study suggests that the program can provide highly accurate estimates of migration rates and individual migrant ancestries, given sufficient genetic differentiation among populations and sufficient numbers of marker loci.

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