Skip to main content
construction release_alert
Scholars@Duke will be undergoing maintenance April 11-15. Some features may be unavailable during this time.
cancel
Journal cover image

Adjusting for covariates on a slippery slope: linkage analysis of change over time.

Publication ,  Journal Article
Rampersaud, E; Allen, A; Li, Y-J; Shao, Y; Bass, M; Haynes, C; Ashley-Koch, A; Martin, ER; Schmidt, S; Hauser, ER
Published in: BMC Genet
December 31, 2003

BACKGROUND: 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 examined methods for incorporating covariates into the linkage analysis. We used methods for quantitative trait loci (QTL) linkage analysis with and without covariates and affected sib-pair (ASP) analysis of hypertension followed by ordered subset analysis (OSA), using variables associated with change in blood pressure over time. RESULTS: Four of the five baseline genes and one of the three slope genes were not detected by any method using conventional criteria. OSA detected baseline gene b35 on chromosome 13 when using the slope in blood pressure to adjust for change over time. Slope gene s10 was detected by the ASP analysis and slope gene s11 was detected by QTL linkage analysis as well as by OSA analysis. Analysis of null chromosomes, i.e., chromosomes without genes, did not reveal significant increases in type I error. However, there were a number of genes indirectly related to blood pressure detected by a variety of methods. CONCLUSIONS: We noted that there is no obvious first choice of analysis software for analyzing a complicated model, such as the one underlying the GAW13 simulated data. Inclusion of covariates and longitudinal data can improve localization of genes for complex traits but it is not always clear how best to do this. It remains a worthwhile task to apply several different approaches since one method is not always the best.

Duke Scholars

Published In

BMC Genet

DOI

EISSN

1471-2156

Publication Date

December 31, 2003

Volume

4 Suppl 1

Issue

Suppl 1

Start / End Page

S50

Location

England

Related Subject Headings

  • Time
  • Software
  • Siblings
  • Quantitative Trait Loci
  • Multifactorial Inheritance
  • Matched-Pair Analysis
  • Longitudinal Studies
  • Hypertension
  • Humans
  • Genetics & Heredity
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Rampersaud, E., Allen, A., Li, Y.-J., Shao, Y., Bass, M., Haynes, C., … Hauser, E. R. (2003). Adjusting for covariates on a slippery slope: linkage analysis of change over time. BMC Genet, 4 Suppl 1(Suppl 1), S50. https://doi.org/10.1186/1471-2156-4-S1-S50
Rampersaud, Evadnie, Andrew Allen, Yi-Ju Li, Yujun Shao, Meredyth Bass, Carol Haynes, Allison Ashley-Koch, Eden R. Martin, Silke Schmidt, and Elizabeth R. Hauser. “Adjusting for covariates on a slippery slope: linkage analysis of change over time.BMC Genet 4 Suppl 1, no. Suppl 1 (December 31, 2003): S50. https://doi.org/10.1186/1471-2156-4-S1-S50.
Rampersaud E, Allen A, Li Y-J, Shao Y, Bass M, Haynes C, et al. Adjusting for covariates on a slippery slope: linkage analysis of change over time. BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S50.
Rampersaud, Evadnie, et al. “Adjusting for covariates on a slippery slope: linkage analysis of change over time.BMC Genet, vol. 4 Suppl 1, no. Suppl 1, Dec. 2003, p. S50. Pubmed, doi:10.1186/1471-2156-4-S1-S50.
Rampersaud E, Allen A, Li Y-J, Shao Y, Bass M, Haynes C, Ashley-Koch A, Martin ER, Schmidt S, Hauser ER. Adjusting for covariates on a slippery slope: linkage analysis of change over time. BMC Genet. 2003 Dec 31;4 Suppl 1(Suppl 1):S50.
Journal cover image

Published In

BMC Genet

DOI

EISSN

1471-2156

Publication Date

December 31, 2003

Volume

4 Suppl 1

Issue

Suppl 1

Start / End Page

S50

Location

England

Related Subject Headings

  • Time
  • Software
  • Siblings
  • Quantitative Trait Loci
  • Multifactorial Inheritance
  • Matched-Pair Analysis
  • Longitudinal Studies
  • Hypertension
  • Humans
  • Genetics & Heredity