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BMC Proceedings

Volume 10 Supplement 7

Genetic Analysis Workshop 19: Sequence, Blood Pressure and Expression Data. Proceedings.

Proceedings

Publication of the proceedings of Genetic Analysis Workshop 19 was supported by National Institutes of Health grant R01 GM031575. Articles have undergone the journal's standard review process for supplements. The Supplement Editors declare that they have no competing interests.

Vienna, Austria24-26 August 2014

Workshop website.

Edited by CMT Greenwood, JW MacCluer and L Almasy.

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  1. Content type: Proceedings

    Genetic Analysis Workshop 19 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence and gene expression data from a pedigree-based sample, as well as whole-exome...

    Authors: Corinne D. Engelman, Celia M. T. Greenwood, Julia N. Bailey, Rita M. Cantor, Jack W. Kent Jr, Inke R. König, Justo Lorenzo Bermejo, Phillip E. Melton, Stephanie A. Santorico, Arne Schillert, Ellen M. Wijsman, Jean W. MacCluer and Laura Almasy

    Citation: BMC Proceedings 2016 10(Suppl 7):19

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  2. Content type: Proceedings

    The Genetic Analysis Workshops (GAW) are a forum for development, testing, and comparison of statistical genetic methods and software. Each contribution to the workshop includes an application to a specified d...

    Authors: John Blangero, Tanya M. Teslovich, Xueling Sim, Marcio A. Almeida, Goo Jun, Thomas D. Dyer, Matthew Johnson, Juan M. Peralta, Alisa Manning, Andrew R. Wood, Christian Fuchsberger, Jack W. Kent Jr, David A. Aguilar, Jennifer E. Below, Vidya S. Farook, Rector Arya…

    Citation: BMC Proceedings 2016 10(Suppl 7):20

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  3. Content type: Proceedings

    We explore causal relationships between genotype, gene expression and phenotype in the Genetic Analysis Workshop 19 data. We compare the use of structural equation modeling and a Bayesian unified framework app...

    Authors: Holly F. Ainsworth and Heather J. Cordell

    Citation: BMC Proceedings 2016 10(Suppl 7):49

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  4. Content type: Proceedings

    Identifying variants that regulate gene expression and delineating their genetic architecture is a critical next step in our endeavors to better understand the genetic etiology of complex diseases. The appropr...

    Authors: Rita M. Cantor, Calvin Pan and Kimberly Siegmund

    Citation: BMC Proceedings 2016 10(Suppl 7):37

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  5. Content type: Proceedings

    Genome-wide microarray expression is a rich source of functional genomic data. We examined evidence for differences in expression from peripheral blood mononuclear cells between individuals, examined some of f...

    Authors: Michael Gallaugher, Angelo J. Canty and Andrew D. Paterson

    Citation: BMC Proceedings 2016 10(Suppl 7):58

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  6. Content type: Proceedings

    We investigate the possible replication of “known” associated single-nucleotide polymorphisms (SNPs) with blood pressure and expression phenotypes. Previous studies have provided a list of 95 SNPs thought to b...

    Authors: Richard A. J. Howey, Jakris Eu-ahsunthornwattana, Rebecca Darlay and Heather J. Cordell

    Citation: BMC Proceedings 2016 10(Suppl 7):28

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  7. Content type: Proceedings

    We present a novel approach to detect potential cis-acting regulatory loci that combines the functional potential, an empirical DNase-seq based estimate of the allele-specificity of DNase-I hypersensitivity sites...

    Authors: Juan Manuel Peralta, Marcio Almeida, Lawrence J. Abraham, Eric Moses and John Blangero

    Citation: BMC Proceedings 2016 10(Suppl 7):50

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  8. Content type: Proceedings

    Expression quantitative trait locus (eQTL) maps are considered a valuable resource in studying complex diseases. The availability of gene expression data from the Genetic Analysis Workshop 19 (GAW19) provides ...

    Authors: Achilleas N. Pitsillides, Seung-Hoan Choi, John D. Hogan, Jaeyoung Hong and Honghuang Lin

    Citation: BMC Proceedings 2016 10(Suppl 7):31

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  9. Content type: Proceedings

    The main focus of the Genetic Analysis Workshop 19 (GAW19) is identification of genes related to the occurrence of hypertension in the cohort of patients with type 2 diabetes mellitus (T2DM). The aim of our st...

    Authors: Piotr Radkowski, Gracjan Wątor, Jan Skupien, Anna Bogdali and Paweł Wołkow

    Citation: BMC Proceedings 2016 10(Suppl 7):64

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  10. Content type: Proceedings

    For a better understanding of the biological mechanisms involved in complex traits or diseases, networks are often useful tools in genetic studies: coexpression networks based on pairwise correlations between ...

    Authors: Renaud Tissier, Hae-Won Uh, Erik van den Akker, Brunilda Balliu, Spyridoula Tsonaka and Jeanine Houwing-Duistermaat

    Citation: BMC Proceedings 2016 10(Suppl 7):35

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  11. Content type: Proceedings

    With the advance of next-generation sequencing technologies, the study of rare variants in targeted genome regions or even the whole genome becomes feasible. Nevertheless, the massive amount of sequencing data...

    Authors: Xiaoran Tong, Changshuai Wei and Qing Lu

    Citation: BMC Proceedings 2016 10(Suppl 7):36

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  12. Content type: Proceedings

    We propose a new method for identifying disease-related regions of single nucleotide variants in recently admixed populations. We use principal component analysis to derive both global and local ancestry infor...

    Authors: Jonathan Auerbach, Michael Agne, Rachel Fan, Adeline Lo, Shaw-Hwa Lo, Tian Zheng and Pei Wang

    Citation: BMC Proceedings 2016 10(Suppl 7):32

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  13. Content type: Proceedings

    Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best prac...

    Authors: Elizabeth Held, Joshua Cape and Nathan Tintle

    Citation: BMC Proceedings 2016 10(Suppl 7):34

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  14. Content type: Proceedings

    Current findings from genetic studies of complex human traits often do not explain a large proportion of the estimated variation of these traits due to genetic factors. This could be, in part, due to overly st...

    Authors: Emily R. Holzinger, Silke Szymczak, James Malley, Elizabeth W. Pugh, Hua Ling, Sean Griffith, Peng Zhang, Qing Li, Cheryl D. Cropp and Joan E. Bailey-Wilson

    Citation: BMC Proceedings 2016 10(Suppl 7):52

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  15. Content type: Proceedings

    With the development of the next-generation sequencing technology, the influence of rare variants on complex disease has gathered increasing attention. In this paper, we propose a clustering-based approach, th...

    Authors: Rui Sun, Qiao Deng, Inchi Hu, Benny Chung-Ying Zee and Maggie Haitian Wang

    Citation: BMC Proceedings 2016 10(Suppl 7):24

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  16. Content type: Proceedings

    Homozygosity disequilibrium (HD) describes a nonrandom pattern of sizable runs of homozygosity (ROH) that deviated from a random distribution of homozygotes and heterozygotes in the genome. In this study, we d...

    Authors: Hsin-Chou Yang and Yu-Ting Lin

    Citation: BMC Proceedings 2016 10(Suppl 7):27

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  17. Content type: Proceedings

    Current rare-variant, gene-based tests of association often suffer from a lack of statistical power to detect genotype–phenotype associations as a result of a lack of prior knowledge of genetic disease models ...

    Authors: Alden Green, Kaitlyn Cook, Kelsey Grinde, Alessandra Valcarcel and Nathan Tintle

    Citation: BMC Proceedings 2016 10(Suppl 7):23

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  18. Content type: Proceedings

    Genome-wide association studies have made substantial progress in identifying common variants associated with human diseases. Despite such success, a large portion of heritability remains unexplained. Evolutio...

    Authors: Sneha Jadhav, Olga A. Vsevolozhskaya, Xiaoran Tong and Qing Lu

    Citation: BMC Proceedings 2016 10(Suppl 7):60

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  19. Content type: Proceedings

    Several statistical group-based approaches have been proposed to detect effects of variation within a gene for each of the population- and family-based designs. However, unified tests to combine gene-phenotype...

    Authors: Yuriko Katsumata and David W. Fardo

    Citation: BMC Proceedings 2016 10(Suppl 7):21

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