Identification of genotype errors

Yin Y. Shugart, Ying Wang

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

It has been documented that there exist some errors in most large genotype datasets and that an error rate of 1-2% is adequate to lead to the distortion of map distance as well as a false conclusion of linkage (Abecasis et al. Eur J Hum Genet 9(2):130-134, 2001), therefore one needs to ensure that the data are as clean as possible. On the other hand, the process of data cleaning is tedious and demands efforts and experience. O'Connell and Weeks implemented four error-checking algorithms in computer software called PedCheck. In this chapter, the four algorithms implemented in PedCheck are discussed with a focus on the genotype-elimination method. Furthermore, an example for four levels of error checking permitted by PedCheck is provided with the required input files. In addition, alternative algorithms implemented in other statistical computing programs are also briefly discussed.

Original languageEnglish (US)
Title of host publicationStatistical Human Genetics
Subtitle of host publicationMethods and Protocols
EditorsRobert Elston, Shuying Sun, Jaya Satagopan
Pages11-24
Number of pages14
DOIs
StatePublished - 2012
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume850
ISSN (Print)1064-3745

Keywords

  • Automatic genotype elimination
  • Computational efficiency
  • Critical-genotype method
  • Genotype
  • Genotype error
  • Genotype-elimination method
  • LOD score
  • Nuclear-pedigree method
  • Odds-ratio method
  • Parametric linkage analysis

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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