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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
Comparison between CARROT and PREST-plus on a set of nine relationships: the height of the bars is the percentage of pairs that were classified incorrectly, so smaller bars are better. In each relationship, the left bar corresponds to PREST-plus and the right bar to CARROT. Avg. is the average error over all relationships examined. (2, 0, 0): full siblings; (1, −1, 0): parent–child; (2, 0, 1): aunt–niece; (1, −1, 1): grandparent–grandchild; (1, 0, 0): half siblings; (2, 1, 1): first cousins; (1, 0, 1): half aunt–niece; (1, 1, 1): half first cousins, unrel: unrelated.
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Figure 4: Comparison between CARROT and PREST-plus on a set of nine relationships: the height of the bars is the percentage of pairs that were classified incorrectly, so smaller bars are better. In each relationship, the left bar corresponds to PREST-plus and the right bar to CARROT. Avg. is the average error over all relationships examined. (2, 0, 0): full siblings; (1, −1, 0): parent–child; (2, 0, 1): aunt–niece; (1, −1, 1): grandparent–grandchild; (1, 0, 0): half siblings; (2, 1, 1): first cousins; (1, 0, 1): half aunt–niece; (1, 1, 1): half first cousins, unrel: unrelated.

Mentions: We also compared CARROT with PREST-plus on the set of nine relationships which includes the seven relationships above as well as half avuncular and half first cousins. As shown in Figure 4, CARROT outperformed PREST-plus for most relationships as well as on average. The only relationship for which CARROT performed worse than PREST-plus was first cousins: 13% of the first cousins pairs were classified as half avuncular by CARROT, probably because the haplo-frequencies of these two relationships are similar.Fig. 4.


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)

Comparison between CARROT and PREST-plus on a set of nine relationships: the height of the bars is the percentage of pairs that were classified incorrectly, so smaller bars are better. In each relationship, the left bar corresponds to PREST-plus and the right bar to CARROT. Avg. is the average error over all relationships examined. (2, 0, 0): full siblings; (1, −1, 0): parent–child; (2, 0, 1): aunt–niece; (1, −1, 1): grandparent–grandchild; (1, 0, 0): half siblings; (2, 1, 1): first cousins; (1, 0, 1): half aunt–niece; (1, 1, 1): half first cousins, unrel: unrelated.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 4: Comparison between CARROT and PREST-plus on a set of nine relationships: the height of the bars is the percentage of pairs that were classified incorrectly, so smaller bars are better. In each relationship, the left bar corresponds to PREST-plus and the right bar to CARROT. Avg. is the average error over all relationships examined. (2, 0, 0): full siblings; (1, −1, 0): parent–child; (2, 0, 1): aunt–niece; (1, −1, 1): grandparent–grandchild; (1, 0, 0): half siblings; (2, 1, 1): first cousins; (1, 0, 1): half aunt–niece; (1, 1, 1): half first cousins, unrel: unrelated.
Mentions: We also compared CARROT with PREST-plus on the set of nine relationships which includes the seven relationships above as well as half avuncular and half first cousins. As shown in Figure 4, CARROT outperformed PREST-plus for most relationships as well as on average. The only relationship for which CARROT performed worse than PREST-plus was first cousins: 13% of the first cousins pairs were classified as half avuncular by CARROT, probably because the haplo-frequencies of these two relationships are similar.Fig. 4.

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