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Related Experiment Video

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Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
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Quality Control for the Illumina HumanExome BeadChip.

Robert P Igo1, Jessica N Cooke Bailey1, Jane Romm2

  • 1Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, Ohio.

Current Protocols in Human Genetics
|July 2, 2016
PubMed
Summary

This study details quality control (QC) procedures for the Illumina HumanExome BeadChip, addressing challenges posed by its focus on rare coding variants. It provides practical solutions for cleaning exome array data in large genetic studies.

Keywords:
Illumina HumanExome BeadChipNEIGHBORHOOD Consortiumexome arraysgenetic association studiesquality control

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Area of Science:

  • Genetics
  • Genomics
  • Bioinformatics

Background:

  • Exome-based genotyping arrays like the Illumina HumanExome BeadChip offer cost-effective genotyping of coding variants.
  • These arrays present unique quality control (QC) challenges due to their non-uniform marker distribution and focus on rare variants.

Purpose of the Study:

  • To describe specific QC procedures for HumanExome BeadChip data.
  • To highlight and address challenges encountered during data cleaning of exome array datasets.

Main Methods:

  • Standard QC procedures for genome-wide array data were adapted.
  • Procedures included genotype calling, sex verification, sample identity verification, relationship checking, and population structure analysis.
  • Data from approximately 7,500 samples from the NEIGHBORHOOD Consortium were used as a case study.

Main Results:

  • The enrichment of rare, exonic variants complicates standard QC.
  • Specific examples of challenges and their resolutions are provided based on practical experience.
  • Effective QC strategies were developed for large-scale exome array data.

Conclusions:

  • Standard QC methods require adaptation for exome-specific arrays.
  • Robust QC is essential for reliable analysis of HumanExome BeadChip data.
  • The described procedures facilitate accurate genetic analyses using exome array data.