@article {664,
	title = {Heterozygosity mapping for human dominant trait variants.},
	journal = {Hum Mutat},
	volume = {40},
	year = {2019},
	month = {2019 07},
	pages = {996-1004},
	abstract = {<p>Homozygosity mapping is a well-known technique to identify runs of homozygous variants that are likely to harbor genes responsible for autosomal recessive disease, but a comparable method for autosomal dominant traits has been lacking. We developed an approach to map dominant disease genes based on heterozygosity frequencies of sequence variants in the immediate vicinity of a dominant trait. We demonstrate through theoretical analysis that DNA variants surrounding an inherited dominant disease variant tend to have increased heterozygosity compared with variants elsewhere in the genome. We confirm existence of this phenomenon in sequence data with known dominant pathogenic variants obtained on family members and in unrelated population controls. A computer-based approach to estimating empirical significance levels associated with our test statistics shows genome-wide p-values smaller than 0.05 for many but not all of the individuals carrying a pathogenic variant.</p>},
	issn = {1098-1004},
	doi = {10.1002/humu.23765},
	author = {Imai-Okazaki, Atsuko and Li, Yi and Horpaopan, Sukanya and Riazalhosseini, Yasser and Garshasbi, Masoud and Mosse, Yael P and Zhang, Di and Schrauwen, Isabelle and Sharma, Aarushi and Fann, Cathy S J and Leal, Suzanne M and Lathrop, Mark and Ott, Jurg}
}
@article {182,
	title = {Genetic linkage analysis in the age of whole-genome sequencing.},
	journal = {Nat Rev Genet},
	volume = {16},
	year = {2015},
	month = {2015 May},
	pages = {275-84},
	abstract = {<p>For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data. </p>},
	keywords = {Algorithms, Female, Genetic Linkage, Genome, Human, Genome-Wide Association Study, Genotyping Techniques, Humans, Lod Score, Male, Pedigree, Penetrance, Phenotype, Polymorphism, Single Nucleotide, Sequence Analysis, DNA, Software},
	issn = {1471-0064},
	doi = {10.1038/nrg3908},
	author = {Ott, Jurg and Wang, Jing and Leal, Suzanne M}
}
