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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Visualization and probability-based scoring of structural variants within repetitive sequences.

Eitan Halper-Stromberg1, Jared Steranka2, Kathleen H Burns1

  • 1Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins Hospital, Department of Pathology, Johns Hopkins University, High Throughput Biology Center, Johns Hopkins University School of Medicine, Johns Hopkins University, Center for Epigenetics, Johns Hopkins University School of Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD and Department of Biostatistics and Computational Biology, Dana Farber Cancer Institute, Boston, Massachusetts, MA, USADepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Program in Human Genetics and Molecular Biology, Johns Hopkins University School of Medicine, Computational Bioscience Program, University of Colorado, Denver, Department of Molecular Biology and Genetics, Department of Oncology, The Sidney Kimmel Comprehensive Cancer Cente

Bioinformatics (Oxford, England)
|February 7, 2014
PubMed
Summary

Analyzing repetitive genomic regions, especially those with rearrangements like Immunoglobulin (Ig) and T-cell receptor (TCR) loci, is challenging for next-generation sequencing. Our new method accurately distinguishes true structural variants from artifacts, improving variant detection in complex genomes.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Molecular Biology

Background:

  • Repetitive sequences comprise about half of the human genome, posing challenges for accurate sequencing.
  • Next-generation sequencing requires specialized analytical techniques for repetitive regions, particularly those with programmed rearrangements such as Immunoglobulin (Ig) and T-cell receptor (TCR) loci.

Purpose of the Study:

  • To develop a robust method for distinguishing true structural variants from alignment artifacts in repetitive genomic regions.
  • To improve the accuracy of variant detection in complex genomic areas, specifically the Ig and TCR loci.

Main Methods:

  • Development of a probability-based scoring and visualization method.
  • Validation using both target-capture and whole-genome sequencing data.
  • Implementation as an R package (targetSeqView) for public accessibility.

Main Results:

  • The developed method effectively separates true structural variants from false positives generated by existing tools.
  • Successful validation across various experimental settings, including primary lymphoid tumors, cancer cell lines, and lymphoblastoid cell lines.
  • Demonstrated utility in analyzing Ig and TCR loci rearrangements.

Conclusions:

  • The new probability-based approach enhances the reliability of structural variant detection in challenging repetitive genomic regions.
  • The targetSeqView R package provides a valuable tool for researchers studying genomic rearrangements in areas like the Ig and TCR loci.