Methods of error detection in genetic linkage data for human pedigrees

Journal Article · Thu Sep 01 04:00:00 EDT 1994 · American Journal of Human Genetics

OSTI ID:133896

Ehm, M G; Kimmel, M ^[1]; Cottingham, R W ^[2]

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1. Rice Univ., Houston, TX (United States)
2. Baylor College of Medicine, Houston, TX (United States)

The occurrence of laboratory typing error in pedigree data collected for use in linkage analysis cannot be ignored. In maps where recombinations between nearby markers rarely occur, each erroneous recombination (result of typing error) is given substantial weight thereby increasing the estimate of theta, the recombination fraction. As the maps being developed become more dense, theta approaches the error rate and most of all observed crossovers will be erroneous. We present two methods for detecting errors in pedigree data. The first index is a variant of the likelihood ratio test statistic and is used to test the null hypothesis of no error for an individual at a locus versus the alternative hypothesis of error. The second index is the conditional likelihood of the data given the phenotype of an individual at a locus. High values of both indices correspond to unlikely genotypes, and p-values can be calculated using simulated distributions under the null hypothesis. Both methods have been shown to detect errors introduced into CEPH pedigrees and an error in a larger experimental pedigree (retinitis pigmentosa). While the methods were designed to detect typing error, they are sufficiently general to detect any relatively unlikely genotype and therefore can also be used to detect pedigree error.

• OSTI ID: 133896
• Report Number(s): CONF-941009--
• Journal Information: American Journal of Human Genetics, Journal Name: American Journal of Human Genetics Journal Issue: Suppl.3 Vol. 55; ISSN AJHGAG; ISSN 0002-9297
• Country of Publication: United States
• Language: English

Related Subjects

55 BIOLOGY AND MEDICINE
BASIC STUDIES
99 GENERAL AND MISCELLANEOUS
ACCURACY
BIOLOGICAL MARKERS
DETECTION
ERRORS
GENE RECOMBINATION
GENETIC MAPPING
GENETICS
GENOTYPE
HEREDITARY DISEASES
PATIENTS
PHENOTYPE
RELIABILITY
STATISTICAL MODELS