title: Methods and Algorithms of Linkage Analysis with quantitative Phenotypes
title: Methoden und Algorithmen der Kopplungsanalyse bei quantitativen Phänotypen
Creators: name: Künzel, Thomas
Publisher: name: Philipps-Universität Marburg
Year: 2012
Subjects: linkage analysis
Biometrie
Medizin, Gesundheit
statistical genetics
quantitative phenotypes
statistische Genetik
GENEHUNTER
Kopplungsanalyse
quantitative Phänotypen
Biostatistik
Biomathematik

description: Motivation: Krankheiten beim
      Menschen werden zu einem großen Teil durch geneti- sche
      Varianten beeinflusst oder verursacht. Um den
      Krankheitsmechanismus zu ver- stehen und um Patienten
      ursächlich behandeln zu können, ist ein erster Schritt, die
      genetische Variante im menschlichen Genom zu lokali Methoden
      um ein mächtiges Verfahren zur genetischen Kartierung
      quantitativer Phänotypen erweitert. Da genehunter-qmod auf
      dem Lander-Green-Algorithmus basiert, können viele Marker
      gleichzeitig in die Kopplungsanalyse einbezogen werden. Darum
      eignet sich genehunter-qmod gut für die Anwendung in
      Genkartierungs- projekten mit diallelischen SNP-Markern, die
      weniger informativ sind als Mikrosatelliten und daher in
      größerer Zahl in die Analyse eingehen müssen. genehunter-qmod
      ist nicht kommerzielle Software und im Internet unter
      http://www.helmholtz-muenchen.de/genepi/downloads frei
      erhältlich.
description: Objective: To a large degree human
      diseases are influenced or caused by genetic variants. In
      order to understand the mechanism of the disease and to treat
      patients in a causative way, a first step is to locate the
      genetic variants in the human genome. An important tool for
      this goal is linkage analysis. In this work, a parametric
      method for linkage analysis of quantitative phenotypes is
      presented. The method provides a test for linkage as well as
      an estimate of different parameters of the genotype-phenotype
      relation.We have implemented our new method in the program
      genehunter-qmod and performed simulations to compare its
      power and type I error to existing methods, i.e. variance
      components analysis (VCA) and Haseman-Elston regression.
      Methods: The phenotype is modeled as a normally distributed
      variable, with a separate distribution for each genotype.
      Estimates of the genotype-specific expectation values and
      standard deviations are obtained by maximizing the LOD score
      over these parameters with a gradient-based optimization
      called pgrad method. That way, genehunter-qmod can both
      locate the putative disease locus and provide specific
      information about the genotype-phenotype relation. Results:
      genehunter-qmod has lower power to detect linkage than VCA in
      ca- se of a normal distribution and with sib pairs. However,
      it outperforms VCA and Haseman-Elston regression for larger
      pedigrees, non-randomly ascertained data or non-normally
      distributed phenotypes. Here, the higher power even goes
      along with conservativeness, while VCA has an inflated type I
      error. Parameter estimation tends to underestimate residual
      variances, but performs better for expectation values of the
      genotype-specific phenotype distributions. Conclusion: With
      genehunter-qmod, a powerful new tool is provided to ex-
      plicitly model quantitative phenotypes in the context of
      linkage analysis. Because genehunter-qmod is based on the
      Lander-Green algorithm, it can simultaneously use many
      markers in the analysis, which makes it applicable to
      gene-mapping projects based on SNP arrays. The program is
      freely available at
      http://www.helmholtz-muenchen.de/genepi/downloads.