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Identifying Cryptic Relationships.

Lei Sun1,2, Apostolos Dimitromanolakis3,4, Wei-Min Chen5,6

  • 1Department of Statistical Sciences, Faculty of Arts and Sciences, University of Toronto, 100 St. George Street, Toronto, ON, Canada, M5S 3G3. sun@utstat.toronto.edu.

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Summary
This summary is machine-generated.

Cryptic relatedness in genetic studies can inflate false positives. This work presents three methods—PREST, PLINK, and KING—to detect and correct for cryptic relatedness in genome-wide association studies (GWAS) and next-generation sequencing (NGS) data.

Keywords:
Cryptic relatednessEM algorithmGWASIBDIBSIISKINGKinship coefficientLikelihoodMethod-of-momentsPLINKPRESTPREST-plusPedigree errorRelationship estimationSequencingSoftware

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Area of Science:

  • Genetics
  • Bioinformatics
  • Population Genetics

Background:

  • Cryptic relatedness, including close familial ties, is frequently encountered in population samples from genome-wide association studies (GWAS) and next-generation sequencing (NGS).
  • This relatedness can erroneously elevate the type 1 error rate in association tests.
  • It also impacts other analyses like population stratification using principal component analysis in GWAS and NGS.

Purpose of the Study:

  • To discuss effective methods for detecting and correcting cryptic relatedness.
  • To highlight the application of these methods using high-throughput SNP data from GWAS and NGS.

Main Methods:

  • Discusses three established methods: PREST, PLINK, and KING.
  • Focuses on their implementation for analyzing single-nucleotide polymorphism (SNP) data.
  • Details analytical and practical aspects of applying these tools.

Main Results:

  • Provides a framework for identifying and managing cryptic relatedness in genetic datasets.
  • Demonstrates the utility of PREST, PLINK, and KING through practical examples.
  • Offers insights into mitigating analytical biases caused by cryptic relatedness.

Conclusions:

  • Effective methods exist to address cryptic relatedness in genetic studies.
  • Utilizing tools like PREST, PLINK, and KING is crucial for accurate GWAS and NGS analysis.
  • Proper handling of cryptic relatedness ensures the reliability of genetic association findings.