Error detection for genetic data, using likelihood methods.

Abstract:

:As genetic maps become denser, the effect of laboratory typing errors becomes more serious. We review a general method for detecting errors in pedigree genotyping data that is a variant of the likelihood-ratio test statistic. It pinpoints individuals and loci with relatively unlikely genotypes. Power and significance studies using Monte Carlo methods are shown by using simulated data with pedigree structures similar to the CEPH pedigrees and a larger experimental pedigree used in the study of idiopathic dilated cardiomyopathy (DCM). The studies show the index detects errors for small values of theta with high power and an acceptable false positive rate. The method was also used to check for errors in DCM laboratory pedigree data and to estimate the error rate in CEPH-chromosome 6 data. The errors flagged by our method in the DCM pedigree were confirmed by the laboratory. The results are consistent with estimated false-positive and false-negative rates obtained using simulation.

journal_name

Am J Hum Genet

authors

Ehm MG,Kimmel M,Cottingham RW Jr

subject

Has Abstract

pub_date

1996-01-01 00:00:00

pages

225-34

issue

1

eissn

0002-9297

issn

1537-6605

journal_volume

58

pub_type

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