Regression models for linkage: Issues of traits, covariates, heterogeneity, and interaction

Daniel J Schaid, Jane M. Olson, W. James Gauderman, Robert C. Elston

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

Regression methods offer a common framework to analyze linkage for quantitative trait loci as well as linkage for affection status using affected sib-pairs. Although numerous papers on regression methods for linkage have been published, some common themes and important caveats tend to be scattered across the literature. For example, the typical approach is to regress a function of traits on identical-by-descent (IBD) information, but the reversal (regression of IBD on a function of traits) offers important insights. A second example is the use of regression equations to assess linkage heterogeneity or gene-environment interaction, and why these two different etiologies are difficult to distinguish with affected sib-pair data. A third example has to do with the differences, and similarities, between linear regression and nonlinear regression methods for affected sib-pair data. The purposes of this paper are to review some recent developments in the linkage regression framework, to emphasize strengths and weaknesses of various proposed methods, and to highlight some important assumptions and caveats.

Original languageEnglish (US)
Pages (from-to)86-96
Number of pages11
JournalHuman Heredity
Volume55
Issue number2-3
DOIs
StatePublished - 2003

Fingerprint

Gene-Environment Interaction
Quantitative Trait Loci
Linear Models

Keywords

  • Haseman and Elston
  • Linear regression
  • Logistic regression
  • Quantitative trait loci
  • Sib-pairs

ASJC Scopus subject areas

  • Genetics(clinical)

Cite this

Regression models for linkage : Issues of traits, covariates, heterogeneity, and interaction. / Schaid, Daniel J; Olson, Jane M.; Gauderman, W. James; Elston, Robert C.

In: Human Heredity, Vol. 55, No. 2-3, 2003, p. 86-96.

Research output: Contribution to journalArticle

Schaid, Daniel J ; Olson, Jane M. ; Gauderman, W. James ; Elston, Robert C. / Regression models for linkage : Issues of traits, covariates, heterogeneity, and interaction. In: Human Heredity. 2003 ; Vol. 55, No. 2-3. pp. 86-96.
@article{350acad248074c3a924d629b5cb71aee,
title = "Regression models for linkage: Issues of traits, covariates, heterogeneity, and interaction",
abstract = "Regression methods offer a common framework to analyze linkage for quantitative trait loci as well as linkage for affection status using affected sib-pairs. Although numerous papers on regression methods for linkage have been published, some common themes and important caveats tend to be scattered across the literature. For example, the typical approach is to regress a function of traits on identical-by-descent (IBD) information, but the reversal (regression of IBD on a function of traits) offers important insights. A second example is the use of regression equations to assess linkage heterogeneity or gene-environment interaction, and why these two different etiologies are difficult to distinguish with affected sib-pair data. A third example has to do with the differences, and similarities, between linear regression and nonlinear regression methods for affected sib-pair data. The purposes of this paper are to review some recent developments in the linkage regression framework, to emphasize strengths and weaknesses of various proposed methods, and to highlight some important assumptions and caveats.",
keywords = "Haseman and Elston, Linear regression, Logistic regression, Quantitative trait loci, Sib-pairs",
author = "Schaid, {Daniel J} and Olson, {Jane M.} and Gauderman, {W. James} and Elston, {Robert C.}",
year = "2003",
doi = "10.1159/000072313",
language = "English (US)",
volume = "55",
pages = "86--96",
journal = "Human Heredity",
issn = "0001-5652",
publisher = "S. Karger AG",
number = "2-3",

}

TY - JOUR

T1 - Regression models for linkage

T2 - Issues of traits, covariates, heterogeneity, and interaction

AU - Schaid, Daniel J

AU - Olson, Jane M.

AU - Gauderman, W. James

AU - Elston, Robert C.

PY - 2003

Y1 - 2003

N2 - Regression methods offer a common framework to analyze linkage for quantitative trait loci as well as linkage for affection status using affected sib-pairs. Although numerous papers on regression methods for linkage have been published, some common themes and important caveats tend to be scattered across the literature. For example, the typical approach is to regress a function of traits on identical-by-descent (IBD) information, but the reversal (regression of IBD on a function of traits) offers important insights. A second example is the use of regression equations to assess linkage heterogeneity or gene-environment interaction, and why these two different etiologies are difficult to distinguish with affected sib-pair data. A third example has to do with the differences, and similarities, between linear regression and nonlinear regression methods for affected sib-pair data. The purposes of this paper are to review some recent developments in the linkage regression framework, to emphasize strengths and weaknesses of various proposed methods, and to highlight some important assumptions and caveats.

AB - Regression methods offer a common framework to analyze linkage for quantitative trait loci as well as linkage for affection status using affected sib-pairs. Although numerous papers on regression methods for linkage have been published, some common themes and important caveats tend to be scattered across the literature. For example, the typical approach is to regress a function of traits on identical-by-descent (IBD) information, but the reversal (regression of IBD on a function of traits) offers important insights. A second example is the use of regression equations to assess linkage heterogeneity or gene-environment interaction, and why these two different etiologies are difficult to distinguish with affected sib-pair data. A third example has to do with the differences, and similarities, between linear regression and nonlinear regression methods for affected sib-pair data. The purposes of this paper are to review some recent developments in the linkage regression framework, to emphasize strengths and weaknesses of various proposed methods, and to highlight some important assumptions and caveats.

KW - Haseman and Elston

KW - Linear regression

KW - Logistic regression

KW - Quantitative trait loci

KW - Sib-pairs

UR - http://www.scopus.com/inward/record.url?scp=0042887051&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0042887051&partnerID=8YFLogxK

U2 - 10.1159/000072313

DO - 10.1159/000072313

M3 - Article

C2 - 12931047

AN - SCOPUS:0042887051

VL - 55

SP - 86

EP - 96

JO - Human Heredity

JF - Human Heredity

SN - 0001-5652

IS - 2-3

ER -