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PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling.

Park DS, Baran Y, Hormozdiari F, Eng C, Torgerson DG, Burchard EG, Zaitlen N - BMC Bioinformatics (2015)

Bottom Line: Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics.IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci.Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult.

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ABSTRACT
Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments.

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Refined IBD true positive rates as a function of LOD score. Refined IBD true positive rates as a function of LOD score are shown as black dots and our converted probabilities as a function of LOD score is shown as a red line.
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Figure 2: Refined IBD true positive rates as a function of LOD score. Refined IBD true positive rates as a function of LOD score are shown as black dots and our converted probabilities as a function of LOD score is shown as a red line.

Mentions: To find the relationship between LOD scores and the true positive rate of IBD segments we ran Refined IBD on simulated data (see Application to simulated data) using a LOD score cutoff of 0.1 and a length cutoff of 0.1 centimorgans. A true positive segment is defined as a predicted segment that is at least 50% true IBD. We fit a curve to the observed relationship between LOD score and true positive rate of IBD segments (see Figure 2). The equation of our curve is of the form p = (2o + af)/(o + f ) where o = posterior odds, f = (prior * (103)/.997)−(prior * (103)), a = (1 − LOD)3/7 if LOD ≤ 1, and a = −0.15 otherwise. The values for f and a were chosen to maximize the fit of the curve.


PIGS: improved estimates of identity-by-descent probabilities by probabilistic IBD graph sampling.

Park DS, Baran Y, Hormozdiari F, Eng C, Torgerson DG, Burchard EG, Zaitlen N - BMC Bioinformatics (2015)

Refined IBD true positive rates as a function of LOD score. Refined IBD true positive rates as a function of LOD score are shown as black dots and our converted probabilities as a function of LOD score is shown as a red line.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4402697&req=5

Figure 2: Refined IBD true positive rates as a function of LOD score. Refined IBD true positive rates as a function of LOD score are shown as black dots and our converted probabilities as a function of LOD score is shown as a red line.
Mentions: To find the relationship between LOD scores and the true positive rate of IBD segments we ran Refined IBD on simulated data (see Application to simulated data) using a LOD score cutoff of 0.1 and a length cutoff of 0.1 centimorgans. A true positive segment is defined as a predicted segment that is at least 50% true IBD. We fit a curve to the observed relationship between LOD score and true positive rate of IBD segments (see Figure 2). The equation of our curve is of the form p = (2o + af)/(o + f ) where o = posterior odds, f = (prior * (103)/.997)−(prior * (103)), a = (1 − LOD)3/7 if LOD ≤ 1, and a = −0.15 otherwise. The values for f and a were chosen to maximize the fit of the curve.

Bottom Line: Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics.IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci.Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Identifying segments in the genome of different individuals that are identical-by-descent (IBD) is a fundamental element of genetics. IBD data is used for numerous applications including demographic inference, heritability estimation, and mapping disease loci. Simultaneous detection of IBD over multiple haplotypes has proven to be computationally difficult. To overcome this, many state of the art methods estimate the probability of IBD between each pair of haplotypes separately. While computationally efficient, these methods fail to leverage the clique structure of IBD resulting in less powerful IBD identification, especially for small IBD segments.

Show MeSH