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Reducing INDEL calling errors in whole genome and exome sequencing data.

Han Fang1, Yiyang Wu2, Giuseppe Narzisi3

  • 1Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY USA ; Stony Brook University, 100 Nicolls Rd, Stony Brook, NY USA ; Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, One Bungtown Road, Cold Spring Harbor, NY USA.

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Summary

Whole genome sequencing (WGS) offers superior accuracy for indel variant calling compared to whole exome sequencing (WES). Optimizing WGS coverage and protocols is crucial for reducing indel errors in genomic studies.

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Area of Science:

  • Genomics
  • Variant Calling
  • Bioinformatics

Background:

  • Insertions and deletions (INDELs) in protein-coding regions are linked to human diseases.
  • INDEL variant calling faces challenges due to library preparation, sequencing biases, and algorithmic artifacts.

Purpose of the Study:

  • To investigate sources of INDEL errors using whole genome sequencing (WGS), whole exome sequencing (WES), and PCR-free sequencing.
  • To develop a classification scheme for ranking INDEL call quality.
  • To compare the accuracy and sensitivity of different sequencing methods for INDEL detection.

Main Methods:

  • Characterization of WGS, WES, and PCR-free sequencing data.
  • Development of a quality classification scheme for INDEL calls.
  • Large-scale validation of 600 loci to assess error rates.

Main Results:

  • Assembly-based callers show higher sensitivity for large INDELs (>5 bp) than alignment-based callers.
  • WGS identifies 10.8-fold more high-quality INDELs than WES, with higher validation rates (84% vs. 57%).
  • PCR-free sequencing improves INDEL detection concordance over standard WGS, and homopolymer A/T INDELs are a major source of low-quality calls, enriched in WES data.

Conclusions:

  • WGS demonstrates significantly greater INDEL detection accuracy than WES, even within targeted exonic regions.
  • A minimum of 60X WGS coverage is recommended for high-sensitivity INDEL recovery, potentially reducing overall project costs.
  • Understanding sources of INDEL errors, such as capture deficiency and homopolymers, is essential for improving genome sequencing accuracy.