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On genomic repeats and reproducibility.

Can Firtina1, Can Alkan1

  • 1Department of Computer Engineering, Bilkent University, Ankara 06800, Turkey.

Bioinformatics (Oxford, England)
|May 7, 2016
PubMed
Summary

Computational genomic variant analysis has reproducibility issues. Algorithms must deterministically handle ambiguous read mappings for accurate and replicable variant discovery from high-throughput sequencing data.

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing (HTS) is crucial for genomic variant discovery.
  • Reproducibility in computational genomics is essential for reliable research.
  • Current variation discovery algorithms may exhibit inconsistencies.

Purpose of the Study:

  • To comprehensively analyze the reproducibility of computational genomic variant characterization.
  • To identify sources of variability in variant calling pipelines.
  • To assess the impact of read mapping ambiguity on variant discovery.

Main Methods:

  • Reanalyzed identical high-throughput sequencing datasets twice with identical tools and parameters.
  • Altered only the order of reads in the input FASTQ files to test reproducibility.

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  • Investigated the effect of read mapping strategies, including scatter/gather approaches.
  • Evaluated variant call set consistency using GATK HaplotypeCaller.

    • Main Results:

    • Read order shuffling in FASTQ files led to different read mappings in repetitive regions.
    • Common variation discovery algorithms inaccurately handle ambiguous read mappings when random locations are chosen.
    • GATK HaplotypeCaller produced slightly different variant call sets even with identical alignments, attributed to the filtration step.

    Conclusions:

    • Genomic variation discovery algorithms require deterministic handling of ambiguous read mappings.
    • Ensuring deterministic mapping is critical for the full replication of variant characterization results.
    • Standardization of algorithms is needed to improve the reproducibility of genomic variant analysis.