Limits...
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
Pedigree for a pair of individuals with two common ancestors: individuals A and B share two MRCAs, C and D. There are genA generations between the MRCAs and A (i.e. genA+1 meioses separating them) and genB generations between the MRCAs and B. The sex of the individuals is arbitrary.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3117348&req=5

Figure 1: Pedigree for a pair of individuals with two common ancestors: individuals A and B share two MRCAs, C and D. There are genA generations between the MRCAs and A (i.e. genA+1 meioses separating them) and genB generations between the MRCAs and B. The sex of the individuals is arbitrary.

Mentions: We defined a set of HMMs for each of three relationship categories similarly to Stankovich et al. (2005) and Bercovici et al. (2010), who defined HMMs for cousins parameterized by the number of generations between them. Unlike these methods, the state space of our models does not increase with the number of generations of the pedigree. Below, we describe our HMMs for the first type of relationships. The models for the other two cases are derived along similar lines. Given that A and B have two MRCAs, C and D (Fig. 1), the hidden state at SNP k depends on the following binary variables:


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)

Pedigree for a pair of individuals with two common ancestors: individuals A and B share two MRCAs, C and D. There are genA generations between the MRCAs and A (i.e. genA+1 meioses separating them) and genB generations between the MRCAs and B. The sex of the individuals is arbitrary.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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

Figure 1: Pedigree for a pair of individuals with two common ancestors: individuals A and B share two MRCAs, C and D. There are genA generations between the MRCAs and A (i.e. genA+1 meioses separating them) and genB generations between the MRCAs and B. The sex of the individuals is arbitrary.
Mentions: We defined a set of HMMs for each of three relationship categories similarly to Stankovich et al. (2005) and Bercovici et al. (2010), who defined HMMs for cousins parameterized by the number of generations between them. Unlike these methods, the state space of our models does not increase with the number of generations of the pedigree. Below, we describe our HMMs for the first type of relationships. The models for the other two cases are derived along similar lines. Given that A and B have two MRCAs, C and D (Fig. 1), the hidden state at SNP k depends on the following binary variables:

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