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NullHap--a versatile application to estimate haplotype frequencies from unphased genotypes in the presence of alleles.

Nowak RM, Płoski R - BMC Bioinformatics (2008)

Bottom Line: Laboratory techniques used to determine haplotypes are often too expensive for large-scale studies and lack of phase information is commonly overcome using likelihood-based calculations.Whereas a number of programs are available for that purpose, none of them can handle loci with both multiple and alleles.Here we present a description of a modified Expectation - Maximization algorithm as well as its implementation (NullHap) which allow to effectively overcome these limitations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Electronics and Information Technology, Institute of Electronic Systems, Warsaw University of Technology, Warsaw, Poland. r.m.nowak@elka.pw.edu.pl

ABSTRACT

Background: Laboratory techniques used to determine haplotypes are often too expensive for large-scale studies and lack of phase information is commonly overcome using likelihood-based calculations. Whereas a number of programs are available for that purpose, none of them can handle loci with both multiple and alleles.

Results: Here we present a description of a modified Expectation - Maximization algorithm as well as its implementation (NullHap) which allow to effectively overcome these limitations. As an example of application we used Nullhap to reanalyze published data on distribution of KIR genotypes in Polish psoriasis patients and controls showing that the KIR2DS4/1D locus may be a marker of KIR2DS1 haplotypes with different effects on disease susceptibility.

Conclusion: The developed application can estimate haplotype frequencies for every type of polymorphism and can effectively be used in genetic research as illustrated by a novel finding regarding the genetic susceptibility to psoriasis.

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Effect of haplotype frequency on the error of the estimation. Effect of haplotype frequency on the error of the estimation. Ten samples of 1000 individuals were generated for population in HWE, for a 2 locus polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The graph shows the error of haplotype frequency estimation in function of assumed frequency of this haplotype.
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Figure 3: Effect of haplotype frequency on the error of the estimation. Effect of haplotype frequency on the error of the estimation. Ten samples of 1000 individuals were generated for population in HWE, for a 2 locus polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The graph shows the error of haplotype frequency estimation in function of assumed frequency of this haplotype.

Mentions: Finally, to evaluate the effect of haplotype frequency on the error of the estimation, 10 samples of 1000 individuals were generated from a population in HWE, for a simple two loci polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The frequencies of haplotypes A0B1, A1B0, A1B1, A2B0, A2B1 were fixed and equal to 0.19, 0.18, 0.16, 0.1, 0.04 and 0.02 respectively, whereas the frequency of haplotype A0B0 varied from 0.05 to 0.9. Results expressed as median of mean absolute percentage error (equation (11)) are shown in Figure 3. As can be seen, the lowest error occured with haplotype frequency close to 0.5.


NullHap--a versatile application to estimate haplotype frequencies from unphased genotypes in the presence of alleles.

Nowak RM, Płoski R - BMC Bioinformatics (2008)

Effect of haplotype frequency on the error of the estimation. Effect of haplotype frequency on the error of the estimation. Ten samples of 1000 individuals were generated for population in HWE, for a 2 locus polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The graph shows the error of haplotype frequency estimation in function of assumed frequency of this haplotype.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2526998&req=5

Figure 3: Effect of haplotype frequency on the error of the estimation. Effect of haplotype frequency on the error of the estimation. Ten samples of 1000 individuals were generated for population in HWE, for a 2 locus polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The graph shows the error of haplotype frequency estimation in function of assumed frequency of this haplotype.
Mentions: Finally, to evaluate the effect of haplotype frequency on the error of the estimation, 10 samples of 1000 individuals were generated from a population in HWE, for a simple two loci polymorphism: A with variants A0, A1, A2 and B with variants B0, B1. The frequencies of haplotypes A0B1, A1B0, A1B1, A2B0, A2B1 were fixed and equal to 0.19, 0.18, 0.16, 0.1, 0.04 and 0.02 respectively, whereas the frequency of haplotype A0B0 varied from 0.05 to 0.9. Results expressed as median of mean absolute percentage error (equation (11)) are shown in Figure 3. As can be seen, the lowest error occured with haplotype frequency close to 0.5.

Bottom Line: Laboratory techniques used to determine haplotypes are often too expensive for large-scale studies and lack of phase information is commonly overcome using likelihood-based calculations.Whereas a number of programs are available for that purpose, none of them can handle loci with both multiple and alleles.Here we present a description of a modified Expectation - Maximization algorithm as well as its implementation (NullHap) which allow to effectively overcome these limitations.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Electronics and Information Technology, Institute of Electronic Systems, Warsaw University of Technology, Warsaw, Poland. r.m.nowak@elka.pw.edu.pl

ABSTRACT

Background: Laboratory techniques used to determine haplotypes are often too expensive for large-scale studies and lack of phase information is commonly overcome using likelihood-based calculations. Whereas a number of programs are available for that purpose, none of them can handle loci with both multiple and alleles.

Results: Here we present a description of a modified Expectation - Maximization algorithm as well as its implementation (NullHap) which allow to effectively overcome these limitations. As an example of application we used Nullhap to reanalyze published data on distribution of KIR genotypes in Polish psoriasis patients and controls showing that the KIR2DS4/1D locus may be a marker of KIR2DS1 haplotypes with different effects on disease susceptibility.

Conclusion: The developed application can estimate haplotype frequencies for every type of polymorphism and can effectively be used in genetic research as illustrated by a novel finding regarding the genetic susceptibility to psoriasis.

Show MeSH
Related in: MedlinePlus