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Reconstruction of genealogical relationships with applications to Phase III of HapMap.

Kyriazopoulou-Panagiotopoulou S, Kashef Haghighi D, Aerni SJ, Sundquist A, Bercovici S, Batzoglou S - Bioinformatics (2011)

Bottom Line: We present CARROT (ClAssification of Relationships with ROTations), a novel framework for relationship inference that leverages linkage information to differentiate between rotated relationships, that is, between relationships with the same number of common ancestors and the same number of meioses separating the individuals under consideration.We demonstrate that CARROT clearly outperforms existing methods on simulated data.We also applied CARROT on four populations from Phase III of the HapMap Project and detected previously unreported pairs of third- and fourth-degree relatives.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA. sofiakp@stanford.edu

ABSTRACT

Motivation: Accurate inference of genealogical relationships between pairs of individuals is paramount in association studies, forensics and evolutionary analyses of wildlife populations. Current methods for relationship inference consider only a small set of close relationships and have limited to no power to distinguish between relationships with the same number of meioses separating the individuals under consideration (e.g. aunt-niece versus niece-aunt or first cousins versus great aunt-niece).

Results: We present CARROT (ClAssification of Relationships with ROTations), a novel framework for relationship inference that leverages linkage information to differentiate between rotated relationships, that is, between relationships with the same number of common ancestors and the same number of meioses separating the individuals under consideration. We demonstrate that CARROT clearly outperforms existing methods on simulated data. We also applied CARROT on four populations from Phase III of the HapMap Project and detected previously unreported pairs of third- and fourth-degree relatives.

Availability: Source code for CARROT is freely available at http://carrot.stanford.edu.

Contact: sofiakp@stanford.edu.

Show MeSH
Illustration of the IBD sharing between a pair of relatives: the horizontal lines represent two haplotypes of individuals A and B and the bold blue box is inherited from an MRCA. The overlapping part of the blue haplotypes is IBD in the two individuals. The first scenario is more likely if A is closer to the MRCA than B.
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Figure 2: Illustration of the IBD sharing between a pair of relatives: the horizontal lines represent two haplotypes of individuals A and B and the bold blue box is inherited from an MRCA. The overlapping part of the blue haplotypes is IBD in the two individuals. The first scenario is more likely if A is closer to the MRCA than B.

Mentions: HMMs that use unlinked markers have limited power to distinguish between relationships of the same degree (Sun et al., 2002). Linkage information can help disambiguate such relationships. Assume, for instance, that we want to determine whether the relationship between individuals A and B is first cousins or great aunt–niece. An IBD block between A and B implies that they inherited overlapping genomic segments from their MRCAs (Fig. 2). If A and B are first cousins, the two scenarios of Figure 2 are equally likely. However, if A is closer to the MRCAs than B, then it is more likely that A inherited a larger segment from the common ancestor than B [scenario (a)], because we expect fewer recombinations between the MRCAs and A than between the MRCAs and B. Therefore, if we compare the haplotypes of A and B in a small window around the IBD transitions to the haplotypes of a reference population, we are more likely to find a match for the haplotype of A, than for the haplotype of B.Fig. 2.


Reconstruction of genealogical relationships with applications to Phase III of HapMap.

Kyriazopoulou-Panagiotopoulou S, Kashef Haghighi D, Aerni SJ, Sundquist A, Bercovici S, Batzoglou S - Bioinformatics (2011)

Illustration of the IBD sharing between a pair of relatives: the horizontal lines represent two haplotypes of individuals A and B and the bold blue box is inherited from an MRCA. The overlapping part of the blue haplotypes is IBD in the two individuals. The first scenario is more likely if A is closer to the MRCA than B.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117348&req=5

Figure 2: Illustration of the IBD sharing between a pair of relatives: the horizontal lines represent two haplotypes of individuals A and B and the bold blue box is inherited from an MRCA. The overlapping part of the blue haplotypes is IBD in the two individuals. The first scenario is more likely if A is closer to the MRCA than B.
Mentions: HMMs that use unlinked markers have limited power to distinguish between relationships of the same degree (Sun et al., 2002). Linkage information can help disambiguate such relationships. Assume, for instance, that we want to determine whether the relationship between individuals A and B is first cousins or great aunt–niece. An IBD block between A and B implies that they inherited overlapping genomic segments from their MRCAs (Fig. 2). If A and B are first cousins, the two scenarios of Figure 2 are equally likely. However, if A is closer to the MRCAs than B, then it is more likely that A inherited a larger segment from the common ancestor than B [scenario (a)], because we expect fewer recombinations between the MRCAs and A than between the MRCAs and B. Therefore, if we compare the haplotypes of A and B in a small window around the IBD transitions to the haplotypes of a reference population, we are more likely to find a match for the haplotype of A, than for the haplotype of B.Fig. 2.

Bottom Line: We present CARROT (ClAssification of Relationships with ROTations), a novel framework for relationship inference that leverages linkage information to differentiate between rotated relationships, that is, between relationships with the same number of common ancestors and the same number of meioses separating the individuals under consideration.We demonstrate that CARROT clearly outperforms existing methods on simulated data.We also applied CARROT on four populations from Phase III of the HapMap Project and detected previously unreported pairs of third- and fourth-degree relatives.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, Biomedical Informatics Training Program, Stanford University School of Medicine, Stanford, CA 94305, USA. sofiakp@stanford.edu

ABSTRACT

Motivation: Accurate inference of genealogical relationships between pairs of individuals is paramount in association studies, forensics and evolutionary analyses of wildlife populations. Current methods for relationship inference consider only a small set of close relationships and have limited to no power to distinguish between relationships with the same number of meioses separating the individuals under consideration (e.g. aunt-niece versus niece-aunt or first cousins versus great aunt-niece).

Results: We present CARROT (ClAssification of Relationships with ROTations), a novel framework for relationship inference that leverages linkage information to differentiate between rotated relationships, that is, between relationships with the same number of common ancestors and the same number of meioses separating the individuals under consideration. We demonstrate that CARROT clearly outperforms existing methods on simulated data. We also applied CARROT on four populations from Phase III of the HapMap Project and detected previously unreported pairs of third- and fourth-degree relatives.

Availability: Source code for CARROT is freely available at http://carrot.stanford.edu.

Contact: sofiakp@stanford.edu.

Show MeSH