Biomaterial Database

Sequential imputation for multilocus linkage analysis. 1994

M Irwin, and N Cox, and A Kong

Department of Statistics, Ohio State University, Columbus 43210-1247.

A Monte Carlo method called sequential imputation is proposed for multilocus likelihood computations. This method is most useful in mapping situations where the data consist of large pedigrees with substantial missing information and it is desirable to perform linkage analysis utilizing data from many polymorphic markers simultaneously. A pedigree example with 155 individuals, 9 loci, and 155,520 haplotypes is used for illustration.

UI	MeSH Term	Description	Entries
D008040	Genetic Linkage	The co-inheritance of two or more non-allelic GENES due to their being located more or less closely on the same CHROMOSOME.	Genetic Linkage Analysis,Linkage, Genetic,Analyses, Genetic Linkage,Analysis, Genetic Linkage,Genetic Linkage Analyses,Linkage Analyses, Genetic,Linkage Analysis, Genetic
D008297	Male		Males
D009010	Monte Carlo Method	In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993)	Method, Monte Carlo
D010375	Pedigree	The record of descent or ancestry, particularly of a particular condition or trait, indicating individual family members, their relationships, and their status with respect to the trait or condition.	Family Tree,Genealogical Tree,Genealogic Tree,Genetic Identity,Identity, Genetic,Family Trees,Genealogic Trees,Genealogical Trees,Genetic Identities,Identities, Genetic,Tree, Family,Tree, Genealogic,Tree, Genealogical,Trees, Family,Trees, Genealogic,Trees, Genealogical
D003924	Diabetes Mellitus, Type 2	A subclass of DIABETES MELLITUS that is not INSULIN-responsive or dependent (NIDDM). It is characterized initially by INSULIN RESISTANCE and HYPERINSULINEMIA; and eventually by GLUCOSE INTOLERANCE; HYPERGLYCEMIA; and overt diabetes. Type II diabetes mellitus is no longer considered a disease exclusively found in adults. Patients seldom develop KETOSIS but often exhibit OBESITY.	Diabetes Mellitus, Adult-Onset,Diabetes Mellitus, Ketosis-Resistant,Diabetes Mellitus, Maturity-Onset,Diabetes Mellitus, Non-Insulin-Dependent,Diabetes Mellitus, Slow-Onset,Diabetes Mellitus, Stable,MODY,Maturity-Onset Diabetes Mellitus,NIDDM,Diabetes Mellitus, Non Insulin Dependent,Diabetes Mellitus, Noninsulin Dependent,Diabetes Mellitus, Noninsulin-Dependent,Diabetes Mellitus, Type II,Maturity-Onset Diabetes,Noninsulin-Dependent Diabetes Mellitus,Type 2 Diabetes,Type 2 Diabetes Mellitus,Adult-Onset Diabetes Mellitus,Diabetes Mellitus, Adult Onset,Diabetes Mellitus, Ketosis Resistant,Diabetes Mellitus, Maturity Onset,Diabetes Mellitus, Slow Onset,Diabetes, Maturity-Onset,Diabetes, Type 2,Ketosis-Resistant Diabetes Mellitus,Maturity Onset Diabetes,Maturity Onset Diabetes Mellitus,Non-Insulin-Dependent Diabetes Mellitus,Noninsulin Dependent Diabetes Mellitus,Slow-Onset Diabetes Mellitus,Stable Diabetes Mellitus
D005260	Female		Females
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D016013	Likelihood Functions	Functions constructed from a statistical model and a set of observed data which give the probability of that data for various values of the unknown model parameters. Those parameter values that maximize the probability are the maximum likelihood estimates of the parameters.	Likelihood Ratio Test,Maximum Likelihood Estimates,Estimate, Maximum Likelihood,Estimates, Maximum Likelihood,Function, Likelihood,Functions, Likelihood,Likelihood Function,Maximum Likelihood Estimate,Test, Likelihood Ratio