Skip to content

Advertisement

Volume 4 Supplement 1

Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors

Proceedings

Edited by Laura Almasy, Christopher I Amos, Joan E Bailey-Wilson, Rita M Cantor, Cashell E Jaquish, Maria Martinez, Rosalind J Neuman, Jane M Olson, Lyle J Palmer, Stephen S Rich, M Anne Spence, Jean W MacCluer

Genetic Analysis Workshop 13: Analysis of Longitudinal Family Data for Complex Diseases and Related Risk Factors. Go to conference site.

New Orleans, LA, USANovember 11-14, 2002

Page 3 of 6
  1. Content type: Proceedings

    The pedigree and genotype data from the Framingham Heart Study were examined for errors. Errors in 21 of 329 pedigrees were detected with the program PREST, and of these the errors in 16 pedigrees were resolve...

    Authors: Gerry Brush and Laura Almasy

    Citation: BMC Genetics 2003 4(Suppl 1):S41

    Published on:

  2. Content type: Proceedings

    Methods to handle missing data have been an area of statistical research for many years. Little has been done within the context of pedigree analysis. In this paper we present two methods for imputing missing ...

    Authors: Brooke Fridley, Kari Rabe and Mariza de Andrade

    Citation: BMC Genetics 2003 4(Suppl 1):S42

    Published on:

  3. Content type: Proceedings

    Missing data are a great concern in longitudinal studies, because few subjects will have complete data and missingness could be an indicator of an adverse outcome. Analyses that exclude potentially informative...

    Authors: Terri Kang, Peter Kraft, W James Gauderman and Duncan Thomas

    Citation: BMC Genetics 2003 4(Suppl 1):S43

    Published on:

  4. Content type: Proceedings

    Observational cohort studies have been little used in linkage analyses due to their general lack of large, disease-specific pedigrees. Nevertheless, the longitudinal nature of such studies makes them potential...

    Authors: Chao Xing, Fredrick R Schumacher, David V Conti and John S Witte

    Citation: BMC Genetics 2003 4(Suppl 1):S44

    Published on:

  5. Content type: Proceedings

    Genetic heterogeneity and complex biologic mechanisms of blood pressure regulation pose significant challenges to the identification of susceptibility loci influencing hypertension. Previous linkage studies ha...

    Authors: Denise Daley, Shannon R Edwards, Yeunjoo Song, Dan Baechle, Sobha Puppala, JH Schick, Jane M Olson and Katrina AB Goddard

    Citation: BMC Genetics 2003 4(Suppl 1):S45

    Published on:

  6. Content type: Proceedings

    We compare two new software packages for linkage analysis, LODPAL and GENEFINDER. Both allow for covariate adjustment. Replicates 1 to 3 of Genetic Analysis Workshop 13 simulated data sets were used for the an...

    Authors: Fang-Chi Hsu, Jacqueline B Hetmanski, Lan Li, Diane Markakis, Kevin Jacobs and Yin Yao Shugart

    Citation: BMC Genetics 2003 4(Suppl 1):S46

    Published on:

  7. Content type: Proceedings

    Plasma triglyceride and high density lipoprotein cholesterol levels are inversely correlated and both are genetically related. Two correlated traits may be influenced both by shared and unshared genes. The pow...

    Authors: Jing-Ping Lin

    Citation: BMC Genetics 2003 4(Suppl 1):S47

    Published on:

  8. Content type: Proceedings

    Family-based association testing is an important part of genetic epidemiology. Tests are available to include multiple siblings, unaffected offspring, and to adjust for environmental covariates. We explore a s...

    Authors: Laila M Poisson, Benjamin A Rybicki, Steven W Coon, Jill S Barnholtz-Sloan and Gary A Chase

    Citation: BMC Genetics 2003 4(Suppl 1):S49

    Published on:

  9. Content type: Proceedings

    We analyzed the Genetic Analysis Workshop 13 (GAW13) simulated data to contrast and compare different methods for the genetic linkage analysis of hypertension and change in blood pressure over time. We also ex...

    Authors: Evadnie Rampersaud, Andrew Allen, Yi-Ju Li, Yujun Shao, Meredyth Bass, Carol Haynes, Allison Ashley-Koch, Eden R Martin, Silke Schmidt and Elizabeth R Hauser

    Citation: BMC Genetics 2003 4(Suppl 1):S50

    Published on:

  10. Content type: Proceedings

    Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that...

    Authors: Rector Arya, Donna Lehman, Kelly J Hunt, Jennifer Schneider, Laura Almasy, John Blangero, Michael P Stern and Ravindranath Duggirala

    Citation: BMC Genetics 2003 4(Suppl 1):S52

    Published on:

  11. Content type: Proceedings

    A standard multivariate principal components (PCs) method was utilized to identify clusters of variables that may be controlled by a common gene or genes (pleiotropy). Heritability estimates were obtained and ...

    Authors: Jeannette T Bensen, Leslie A Lange, Carl D Langefeld, Bao-Li Chang, Eugene R Bleecker, Deborah A Meyers and Jianfeng Xu

    Citation: BMC Genetics 2003 4(Suppl 1):S53

    Published on:

  12. Content type: Proceedings

    We used an approach for detecting genotype × environment interactions to detect and characterize genotype × age interaction in longitudinal measures of three well known cardiovascular risk factors: total plasm...

    Authors: LM Havill and MC Mahaney

    Citation: BMC Genetics 2003 4(Suppl 1):S54

    Published on:

  13. Content type: Proceedings

    Multivariate variance-components analysis provides several advantages over univariate analysis when studying correlated traits. It can test for pleiotropy or (in the longitudinal context) gene × age interactio...

    Authors: Peter Kraft, Lara Bauman, Jin Ying Yuan and Steve Horvath

    Citation: BMC Genetics 2003 4(Suppl 1):S55

    Published on:

  14. Content type: Proceedings

    Using the simulated data set from Genetic Analysis Workshop 13, we explored the advantages of using longitudinal data in genetic analyses. The weighted average of the longitudinal data for each of seven quanti...

    Authors: Nathan Pankratz, Nitai Mukhopadhyay, Shuguang Huang, Tatiana Foroud and Sandra Close Kirkwood

    Citation: BMC Genetics 2003 4(Suppl 1):S58

    Published on:

  15. Content type: Proceedings

    We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting gluco...

    Authors: Ayse Ulgen, Zhihua Han and Wentian Li

    Citation: BMC Genetics 2003 4(Suppl 1):S60

    Published on:

Page 3 of 6

2017 Journal Metrics

Portable Peer Review

The editors of BMC Genetics support initiatives that expedite the peer review process and are happy to consider manuscripts that have been reviewed in Peerage of Science. Please indicate in your cover letter if this applies to your manuscript.

Peerage of Science logo
blank

Advertisement