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Fast all versus all genotype comparison using DNA/RNA sequencing data: method and workflow.

Steven A Eschrich1, Xiaoqing Yu1, Jamie K Teer2

  • 1Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.

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|April 24, 2023
PubMed
Summary
This summary is machine-generated.

Prevent sample mix-ups in sequencing with a new, efficient tool. This method rapidly compares all genotypes to identify and resolve sample swaps, ensuring accurate genomic data.

Keywords:
Genotype comparisonMassively parallel sequencingQuality control

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Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Massively parallel sequencing involves liquid handling steps that can lead to sample swaps, mixing, and duplication.
  • Inherited genomic variants can be used to verify sample identity through sequence data comparison.
  • All-to-all sample comparison aids in identifying mismatched samples and resolving swaps, but computational complexity increases quadratically with sample number.

Purpose of the Study:

  • To develop an efficient computational tool for all-to-all genotype comparison to ensure sample identity in sequencing studies.

Main Methods:

  • Developed a fast all-to-all genotype comparison tool utilizing low-level bitwise operations in Perl.
  • Integrated a complete workflow to process raw FASTQ, aligned BAM, or genotype VCF files.
  • Automated generation of comparison metrics and summary plots.

Main Results:

  • The tool provides efficient all-to-all genotype comparison.
  • The workflow supports multiple input file types (FASTQ, BAM, VCF).
  • Summary plots and comparison metrics are automatically generated.

Conclusions:

  • A fast and user-friendly genotype comparison method is crucial for high-quality sequencing study results.
  • This tool enhances the robustness and reliability of genomic data by ensuring sample integrity.