Literature DB >> 6573130

Evaluating pedigree data. I. The estimation of pedigree error in the presence of marker mistyping.

G M Lathrop, A B Hooper, J W Huntsman, R H Ward.   

Abstract

Pedigrees used in the analysis of genetic or medical data are usually ascertained from sources subject to a variety of errors including misidentification of individuals, faults in historical documents or record linkage, nonpaternity, and unidentified adoption. Genetic markers can be used to verify putative family and pedigree data through the search for inconsistencies, or genetic exclusions, between putative parents and offspring. The probability of observing an exclusion given the occurrence of an error depends upon the gene frequencies at the loci under study and the forms of error. In addition, inconsistencies can arise from laboratory errors in marker determination. Together, these problems make the proper statistical analysis of such data desirable. Here we give a model that specifies the combined effects of various kinds of pedigree error along with genetic marker error. This model allows the maximum-likelihood estimation of the rates of various forms of pedigree error and laboratory error from genetic marker data collected on putative families. The method is illustrated by applying it to data obtained from a South Pacific island population, Tokelau. From the observed distribution of genetic marker inconsistencies between the parents and offspring of putative families, derived from the extensive genealogy of this population, we are able to estimate that the error of a paternal link is 4%, the error of a maternal link is zero, and the overall system typing error is 1%.

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Year:  1983        PMID: 6573130      PMCID: PMC1685535     

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  17 in total

1.  STUDIES ON THE XAVANTE INDIANS OF THE BRAZILIAN MATO GROSSO.

Authors:  J V NEEL; F M SALZANO; P C JUNQUEIRA; F KEITER; D MAYBURY-LEWIS
Journal:  Am J Hum Genet       Date:  1964-03       Impact factor: 11.025

2.  Tables and nomogram for calculating chances of excluding paternity.

Authors:  W C BOYD
Journal:  Am J Hum Genet       Date:  1954-12       Impact factor: 11.025

3.  The estimation of pairwise relationships.

Authors:  E A Thompson
Journal:  Ann Hum Genet       Date:  1975-10       Impact factor: 1.670

4.  On the Estimation of the Frequency of Nonpaternity.

Authors:  J W Maccluer; W J Schull
Journal:  Am J Hum Genet       Date:  1963-06       Impact factor: 11.025

5.  The Tokelau Island migrant study.

Authors:  I A Prior; J M Stanhope; J G Evans; C E Salmond
Journal:  Int J Epidemiol       Date:  1974-09       Impact factor: 7.196

6.  Exclusion of paternity: the current state of the art.

Authors:  R Chakraborty; M Shaw; W J Schull
Journal:  Am J Hum Genet       Date:  1974-07       Impact factor: 11.025

7.  A general model for the genetic analysis of pedigree data.

Authors:  R C Elston; J Stewart
Journal:  Hum Hered       Date:  1971       Impact factor: 0.444

8.  Probability calculations in pedigrees under complex modes of inheritance.

Authors:  J M Lalouel
Journal:  Hum Hered       Date:  1980       Impact factor: 0.444

9.  Studies on genetic selection in a completely ascertained caucasian population. II. Family analyses of 11 blood group systems.

Authors:  C F Sing; D C Shreffler; J V Neel; J A Napier
Journal:  Am J Hum Genet       Date:  1971-03       Impact factor: 11.025

10.  Probability of paternity exclusion when relatives are involved.

Authors:  D B Salmon; J Brocteur
Journal:  Am J Hum Genet       Date:  1978-01       Impact factor: 11.025

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  18 in total

1.  A multipoint method for detecting genotyping errors and mutations in sibling-pair linkage data.

Authors:  J A Douglas; M Boehnke; K Lange
Journal:  Am J Hum Genet       Date:  2000-03-28       Impact factor: 11.025

2.  Linkage analysis in the presence of errors III: marker loci and their map as nuisance parameters.

Authors:  H H Göring; J D Terwilliger
Journal:  Am J Hum Genet       Date:  2000-03-23       Impact factor: 11.025

3.  Detection and integration of genotyping errors in statistical genetics.

Authors:  Eric Sobel; Jeanette C Papp; Kenneth Lange
Journal:  Am J Hum Genet       Date:  2002-01-08       Impact factor: 11.025

4.  Linkage analysis in the presence of errors II: marker-locus genotyping errors modeled with hypercomplex recombination fractions.

Authors:  H H Göring; J D Terwilliger
Journal:  Am J Hum Genet       Date:  2000-03       Impact factor: 11.025

5.  A high-density screen for linkage in multiple sclerosis.

Authors:  Stephen Sawcer; Maria Ban; Mel Maranian; Tai Wai Yeo; Alastair Compston; Andrew Kirby; Mark J Daly; Philip L De Jager; Emily Walsh; Eric S Lander; John D Rioux; David A Hafler; Adrian Ivinson; Jacqueline Rimmler; Simon G Gregory; Silke Schmidt; Margaret A Pericak-Vance; Eva Akesson; Jan Hillert; Pameli Datta; Annette Oturai; Lars P Ryder; Hanne F Harbo; Anne Spurkland; Kjell-Morten Myhr; Mikko Laaksonen; David Booth; Robert Heard; Graeme Stewart; Robin Lincoln; Lisa F Barcellos; Stephen L Hauser; Jorge R Oksenberg; Shannon J Kenealy; Jonathan L Haines
Journal:  Am J Hum Genet       Date:  2005-07-29       Impact factor: 11.025

6.  PedCheck: a program for identification of genotype incompatibilities in linkage analysis.

Authors:  J R O'Connell; D E Weeks
Journal:  Am J Hum Genet       Date:  1998-07       Impact factor: 11.025

7.  A test statistic to detect errors in sib-pair relationships.

Authors:  M Ehm; M Wagner
Journal:  Am J Hum Genet       Date:  1998-01       Impact factor: 11.025

8.  Identifying marker typing incompatibilities in linkage analysis.

Authors:  H M Stringham; M Boehnke
Journal:  Am J Hum Genet       Date:  1996-10       Impact factor: 11.025

9.  Considerations in using linkage analysis as a presymptomatic test for Huntington's disease.

Authors:  L A Farrer; R H Myers; L A Cupples; P M Conneally
Journal:  J Med Genet       Date:  1988-09       Impact factor: 6.318

Review 10.  Measuring paternal discrepancy and its public health consequences.

Authors:  Mark A Bellis; Karen Hughes; Sara Hughes; John R Ashton
Journal:  J Epidemiol Community Health       Date:  2005-09       Impact factor: 3.710

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