@article {631,
	title = {Enrolling Genomics Research Participants through a Clinical Setting: the Impact of Existing Clinical Relationships on Informed Consent and Expectations for Return of Research Results.},
	journal = {J Genet Couns},
	volume = {27},
	year = {2018},
	month = {2018 02},
	pages = {263-273},
	abstract = {<p>Genetic counselors working in a clinical setting may find themselves recruiting, enrolling, and returning results for genomic research, and existing clinical relationships with study participants may impact these research interactions. We present a qualitative study using semi-structured interviews of participants enrolled in a genome sequencing/exome sequencing (GS/ES) study at the same institution where they receive clinical care. Interviews were coded for motivations to participate and expectations of this research. The interviews revealed common motivations for participation, including altruism and hope for benefit for themselves, family members, and/or others with their condition. Additionally, themes emerged related to unintentional influence based on trust of the clinical provider that recruited them to the study. Participant trust in the enrolling provider at times appeared to extend to the study team to decide which research results to return and to do so in an appropriate format. Participants also based expectations for research results return on previous clinical genetic testing experiences, which may or may not be realistic depending on study design. It is imperative that genetic counselors enrolling patients into research studies be aware of the potential influence of their clinical relationship on potential subjects, be transparent about their role on the study team, and help set expectations about the study process, including results return.</p>},
	keywords = {Base Sequence, Decision Making, Family, Female, Genetic Testing, Humans, Informed Consent, Male, Motivation, Qualitative Research, Research Design, Trust},
	issn = {1573-3599},
	doi = {10.1007/s10897-017-0143-2},
	author = {Berrios, Courtney and James, Cynthia A and Raraigh, Karen and Bollinger, Juli and Murray, Brittney and Tichnell, Crystal and Applegate, Carolyn D and Bergner, Amanda L}
}
@article {415,
	title = {Increasing Generality and Power of Rare-Variant Tests by Utilizing Extended Pedigrees.},
	journal = {Am J Hum Genet},
	volume = {99},
	year = {2016},
	month = {2016 Oct 06},
	pages = {846-859},
	abstract = {<p>Recently, multiple studies have performed whole-exome or whole-genome sequencing to identify groups of rare variants associated with complex traits and diseases. They have primarily utilized case-control study designs that often require thousands of individuals to reach acceptable statistical power. Family-based studies can be more powerful because a rare variant can be enriched in an extended pedigree and segregate with the phenotype. Although many methods have been proposed for using family data to discover rare variants involved in a disease, a majority of them focus on a specific pedigree structure and are designed to analyze either binary or continuously measured outcomes. In this article, we propose RareIBD, a general and powerful approach to identifying rare variants involved in disease susceptibility. Our method can be applied to large extended families of arbitrary structure, including pedigrees with only affected individuals. The method accommodates both binary and quantitative traits. A series of simulation experiments suggest that RareIBD is a powerful test that outperforms existing approaches. In addition, our method accounts for individuals in top generations, which are not usually genotyped in extended families. In contrast to available statistical tests, RareIBD generates accurate p values even when genetic data from these individuals are missing. We applied RareIBD, as well as other methods, to two extended family datasets generated by different genotyping technologies and representing different ethnicities. The analysis of real data confirmed that RareIBD is the only method that properly controls type I error.</p>},
	keywords = {Datasets as Topic, Ethnic Groups, Family, Female, Genetic Predisposition to Disease, Genetic Variation, Genotype, Humans, Male, Models, Genetic, Pedigree, Phenotype, Research Design},
	issn = {1537-6605},
	doi = {10.1016/j.ajhg.2016.08.015},
	author = {Sul, Jae Hoon and Cade, Brian E and Cho, Michael H and Qiao, Dandi and Silverman, Edwin K and Redline, Susan and Sunyaev, Shamil}
}
