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BMC Genetics

Volume 17 Supplement 2

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

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

 Edited by CMT Greenwood, JW MacCluer and L Almasy.

  1. Content type: Proceedings

    This paper summarizes the contributions from the Population-Based Association group at the Genetic Analysis Workshop 19. It provides an overview of the new statistical approaches tried out by group members in ...

    Authors: Justo Lorenzo Bermejo

    Citation: BMC Genetics 2016 17(Suppl 2):S2

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  2. Content type: Proceedings

    We currently have the ability to quantify transcript abundance of messenger RNA (mRNA), genome-wide, using microarray technologies. Analyzing genotype, phenotype and expression data from 20 pedigrees, the memb...

    Authors: Rita M. Cantor and Heather J. Cordell

    Citation: BMC Genetics 2016 17(Suppl 2):S3

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  3. Content type: Proceedings

    Longitudinal phenotypic data provides a rich potential resource for genetic studies which may allow for greater understanding of variants and their covariates over time. Herein, we review 3 longitudinal analyt...

    Authors: Yen-Feng Chiu, Anne E. Justice and Phillip E. Melton

    Citation: BMC Genetics 2016 17(Suppl 2):S4

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  4. Content type: Proceedings

    High-density genetic marker data, especially sequence data, imply an immense multiple testing burden. This can be ameliorated by filtering genetic variants, exploiting or accounting for correlations between va...

    Authors: Stefanie Friedrichs, Dörthe Malzahn, Elizabeth W. Pugh, Marcio Almeida, Xiao Qing Liu and Julia N. Bailey

    Citation: BMC Genetics 2016 17(Suppl 2):S8

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  5. Content type: Research

    New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation andpenalties for multiple testing.

    Authors: Jack W. Kent Jr

    Citation: BMC Genetics 2016 17(Suppl 2):S5

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  6. Content type: Proceedings

    In the analysis of current genomic data, application of machine learning and data mining techniques has become more attractive given the rising complexity of the projects. As part of the Genetic Analysis Works...

    Authors: Inke R. König, Jonathan Auerbach, Damian Gola, Elizabeth Held, Emily R. Holzinger, Marc-André Legault, Rui Sun, Nathan Tintle and Hsin-Chou Yang

    Citation: BMC Genetics 2016 17(Suppl 2):S1

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  7. Content type: Proceedings

    Empirical studies and evolutionary theory support a role for rare variants in the etiology of complex traits. Given this motivation and increasing affordability of whole-exome and whole-genome sequencing, meth...

    Authors: Stephanie A. Santorico and Audrey E. Hendricks

    Citation: BMC Genetics 2016 17(Suppl 2):S6

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