Gaussian models for genetic linkage analysis using complete high-resolution maps of identity by descent

Journal Article · Thu Jul 01 00:00:00 EDT 1993 · American Journal of Human Genetics; (United States)

OSTI ID:5957458

Feingold, E; Siegmund, D; Brown, P O ^[1]

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1. Howard Hughes Medical Institute, Stanford Univ. (United States)

Gaussian-process models are developed to detect genetic linkage using complete high-resolution maps of identity by descent between affected relative pairs. Approximations are given for the significance level and power of the likelihood-ratio test of no linkage and for likelihood-ratio confidence regions for trait loci. The sample sizes required to detect linkage by using different classes of affected relative pairs are compared, and the problem of combining data from different classes of relatives is discussed. 23 refs., 2 figs.

• OSTI ID: 5957458
• Journal Information: American Journal of Human Genetics; (United States), Vol. 53:1; ISSN 0002-9297
• Country of Publication: United States
• Language: English

Related Subjects

59 BASIC BIOLOGICAL SCIENCES
GENES
GENETIC MAPPING
GAUSSIAN PROCESSES
STATISTICAL MODELS
BIOLOGICAL MARKERS
GAUSS FUNCTION
MATHEMATICAL MODELS
MAXIMUM-LIKELIHOOD FIT
RFLPS
FUNCTIONS
MAPPING
NUMERICAL SOLUTION
550400* - Genetics