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Related Experiment Video

Updated: Sep 26, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
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The COPILOT Raw Illumina Genotyping QC Protocol.

Hamel Patel1,2, Sang-Hyuck Lee2,3, Gerome Breen2,3

  • 1Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, UK.

Current Protocols
|April 22, 2022
PubMed
Summary
This summary is machine-generated.

The COPILOT protocol streamlines raw Illumina genotyping data processing using GenomeStudio and a containerized pipeline. It automates complex bioinformatics analyses, improving data quality and identifying common issues for GWAS studies.

Keywords:
GWASIlluminaQC pipelinedockergenotyping

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Illumina genotyping microarrays generate complex raw data requiring extensive bioinformatics analysis.
  • Current methods are time-consuming, prone to reproducibility errors, and pose challenges for bioinformaticians.
  • Processing large-scale human patient sample data requires robust and efficient pipelines.

Purpose of the Study:

  • To introduce the COPILOT protocol for transforming raw Illumina genotype intensity data into analysis-ready data.
  • To automate complex bioinformatics analyses and improve the quality of genotyping data.
  • To facilitate the identification of common data issues in Genome-Wide Association Study (GWAS) datasets.

Main Methods:

  • The COPILOT protocol employs two tandem procedures: GenomeStudio for initial QC and a containerized pipeline (COPILOT) for advanced analysis.
  • The containerized workflow automates secondary clustering, gender discrepancy checks, heterozygosity outlier identification, relatedness estimation, and population stratification.
  • Data is processed for various Illumina genotyping arrays, including custom content chips with millions of markers.

Main Results:

  • Successfully transformed raw Illumina genotyping data into high-quality, analysis-ready data for tens of thousands of human samples.
  • Automated identification of typical GWAS data issues, including gender, heterozygosity, relatedness, and population outliers.
  • Output data is provided in PLINK binary format with a comprehensive HTML summary report.

Conclusions:

  • The COPILOT protocol offers an efficient and reproducible solution for processing raw Illumina genotyping data.
  • It significantly enhances data quality and facilitates downstream analyses like GWAS.
  • The protocol and pipeline are publicly available, promoting wider adoption in genomic research.