Relatedness ----------- .. currentmodule:: hail.methods The *relatedness* of two individuals characterizes their biological relationship. For example, two individuals might be siblings or parent-and-child. All notions of relatedness implemented in Hail are rooted in the idea of alleles "inherited identically by descent". Two alleles in two distinct individuals are inherited identically by descent if both alleles were inherited by the same "recent," common ancestor. The term "recent" distinguishes alleles shared IBD from family members from alleles shared IBD from "distant" ancestors. Distant ancestors are thought of contributing to population structure rather than relatedness. Relatedness is usually quantified by two quantities: kinship coefficient (:math:`\phi` or ``PI_HAT``) and probability-of-identity-by-descent-zero (:math:`\pi_0` or ``Z0``). The kinship coefficient is the probability that any two alleles selected randomly from the same locus are identical by descent. Twice the kinship coefficient is the coefficient of relationship which is the percent of genetic material shared identically by descent. Probability-of-identity-by-descent-zero is the probability that none of the alleles at a randomly chosen locus were inherited identically by descent. Hail provides three methods for the inference of relatedness: PLINK-style identity by descent [1]_, KING [2]_, and PC-Relate [3]_. - :func:`.identity_by_descent` is appropriate for datasets containing one homogeneous population. - :func:`.king` is appropriate for datasets containing multiple homogeneous populations and no admixture. It is also used to prune close relatives before using :func:`.pc_relate`. - :func:`.pc_relate` is appropriate for datasets containing multiple homogeneous populations and admixture. .. toctree:: :maxdepth: 2 .. autosummary:: identity_by_descent king pc_relate simulate_random_mating .. autofunction:: identity_by_descent .. autofunction:: king .. autofunction:: pc_relate .. autofunction:: simulate_random_mating .. [1] Purcell, Shaun et al. “PLINK: a tool set for whole-genome association and population-based linkage analyses.” American journal of human genetics vol. 81,3 (2007): 559-75. doi:10.1086/519795. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1950838/ .. [2] Manichaikul, Ani et al. “Robust relationship inference in genome-wide association studies.” Bioinformatics (Oxford, England) vol. 26,22 (2010): 2867-73. doi:10.1093/bioinformatics/btq559. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3025716/ .. [3] Conomos, Matthew P et al. “Model-free Estimation of Recent Genetic Relatedness.” American journal of human genetics vol. 98,1 (2016): 127-48. doi:10.1016/j.ajhg.2015.11.022. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4716688/