@article {595,
	title = {Insights into genetics, human biology and disease gleaned from family based genomic studies.},
	journal = {Genet Med},
	volume = {21},
	year = {2019},
	month = {2019 04},
	pages = {798-812},
	abstract = {<p>Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75\% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in~novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.</p>},
	keywords = {Databases, Genetic, Genetic Diseases, Inborn, Genetic Heterogeneity, Genetic Predisposition to Disease, Genome, Human, Genomics, Humans, National Institutes of Health (U.S.), Pedigree, United States, Whole Exome Sequencing},
	issn = {1530-0366},
	doi = {10.1038/s41436-018-0408-7},
	author = {Posey, Jennifer E and O{\textquoteright}Donnell-Luria, Anne H and Chong, Jessica X and Harel, Tamar and Jhangiani, Shalini N and Coban Akdemir, Zeynep H and Buyske, Steven and Pehlivan, Davut and Carvalho, Claudia M B and Baxter, Samantha and Sobreira, Nara and Liu, Pengfei and Wu, Nan and Rosenfeld, Jill A and Kumar, Sushant and Avramopoulos, Dimitri and White, Janson J and Doheny, Kimberly F and Witmer, P Dane and Boehm, Corinne and Sutton, V Reid and Muzny, Donna M and Boerwinkle, Eric and G{\"u}nel, Murat and Nickerson, Deborah A and Mane, Shrikant and MacArthur, Daniel G and Gibbs, Richard A and Hamosh, Ada and Lifton, Richard P and Matise, Tara C and Rehm, Heidi L and Gerstein, Mark and Bamshad, Michael J and Valle, David and Lupski, James R}
}
@article {193,
	title = {New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene.},
	journal = {Hum Mutat},
	volume = {36},
	year = {2015},
	month = {2015 Apr},
	pages = {425-31},
	abstract = {<p>Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s). </p>},
	keywords = {Computational Biology, Databases, Genetic, Genetic Association Studies, Genetic Diseases, Inborn, Genetic Variation, Genomics, Internet, Phenotype, Software, Web Browser},
	issn = {1098-1004},
	doi = {10.1002/humu.22769},
	author = {Sobreira, Nara and Schiettecatte, Fran{\c c}ois and Boehm, Corinne and Valle, David and Hamosh, Ada}
}
