Genetic Epidemiology, Translational Neurogenomics, Psychiatric Genetics and Statistical Genetics Laboratories investigate the pattern of disease in families, particularly identical and non-identical twins, to assess the relative importance of genes and environment in a variety of important health problems.
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PMID
8651312
TITLE
Parametric and nonparametric linkage analysis: a unified multipoint approach.
ABSTRACT
In complex disease studies, it is crucial to perform multipoint linkage analysis with many markers and to use robust nonparametric methods that take account of all pedigree information. Currently available methods fall short in both regards. In this paper, we describe how to extract complete multipoint inheritance information from general pedigrees of moderate size. This information is captured in the multipoint inheritance distribution, which provides a framework for a unified approach to both parametric and nonparametric methods of linkage analysis. Specifically, the approach includes the following: (1) Rapid exact computation of multipoint LOD scores involving dozens of highly polymorphic markers, even in the presence of loops and missing data. (2) Non-parametric linkage (NPL) analysis, a powerful new approach to pedigree analysis. We show that NPL is robust to uncertainty about mode of inheritance, is much more powerful than commonly used nonparametric methods, and loses little power relative to parametric linkage analysis. NPL thus appears to be the method of choice for pedigree studies of complex traits. (3) Information-content mapping, which measures the fraction of the total inheritance information extracted by the available marker data and points out the regions in which typing additional markers is most useful. (4) Maximum-likelihood reconstruction of many-marker haplotypes, even in pedigrees with missing data. We have implemented NPL analysis, LOD-score computation, information-content mapping, and haplotype reconstruction in a new computer package, GENEHUNTER. The package allows efficient multipoint analysis of pedigree data to be performed rapidly in a single user-friendly environment.
DATE PUBLISHED
1996 Jun
HISTORY
PUBSTATUS PUBSTATUSDATE
pubmed 1996/06/01
medline 1996/06/01 00:01
entrez 1996/06/01 00:00
AUTHORS
NAME COLLECTIVENAME LASTNAME FORENAME INITIALS AFFILIATION AFFILIATIONINFO
Kruglyak L Kruglyak L L Whitehead Institute for Biomedical Research, Cambridge. leonid@genome.wi.mit.edu
Daly MJ Daly M J MJ
Reeve-Daly MP Reeve-Daly M P MP
Lander ES Lander E S ES
INVESTIGATORS
JOURNAL
VOLUME: 58
ISSUE: 6
TITLE: American journal of human genetics
ISOABBREVIATION: Am. J. Hum. Genet.
YEAR: 1996
MONTH: Jun
DAY:
MEDLINEDATE:
SEASON:
CITEDMEDIUM: Print
ISSN: 0002-9297
ISSNTYPE: Print
MEDLINE JOURNAL
MEDLINETA: Am J Hum Genet
COUNTRY: United States
ISSNLINKING: 0002-9297
NLMUNIQUEID: 0370475
PUBLICATION TYPE
PUBLICATIONTYPE TEXT
Comparative Study
Journal Article
Research Support, U.S. Gov't, P.H.S.
COMMENTS AND CORRECTIONS
GRANTS
GRANTID AGENCY COUNTRY
HG00017 NHGRI NIH HHS United States
HG00098 NHGRI NIH HHS United States
GENERAL NOTE
KEYWORDS
MESH HEADINGS
DESCRIPTORNAME QUALIFIERNAME
Algorithms
Female
Genes, Dominant
Genetic Diseases, Inborn genetics
Genetic Linkage genetics
Haplotypes genetics
Humans genetics
Lod Score genetics
Male genetics
Models, Genetic genetics
Models, Statistical genetics
Pedigree genetics
Reproducibility of Results genetics
Schizophrenia genetics
Software genetics
Statistics, Nonparametric genetics
SUPPLEMENTARY MESH
GENE SYMBOLS
CHEMICALS
OTHER ID's