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The first human genome sequencing project cost $2.7 billion and was declared complete in 2003, after 15 years of international cooperation and collaboration between several research teams and funding agencies. Today, with the advent of next-generation sequencing technologies, the cost and time of sequencing a human genome have dropped over 100 fold.
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Although all next-generation methods use different technologies, they all share a set of standard features....
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Targeted DNA Methylation Analysis by Next-generation Sequencing
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Transmission Disequilibrium Tests Based on Read Counts for Low-Coverage Next-Generation Sequence Data.

Wonkuk Kim1

  • 1Department of Applied Statistics, Chung-Ang University, Seoul, South Korea.

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This study introduces novel statistical methods for next-generation sequencing (NGS) case-parent trio association studies, effectively incorporating low-coverage data without genotype imputation. The new methods offer improved power and control type I error rates for genetic association analysis.

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Area of Science:

  • Genetics
  • Statistical Genetics
  • Bioinformatics

Background:

  • Case-parent trio studies are crucial for genetic association analysis.
  • Next-generation sequencing (NGS) generates read count data, often with low coverage.
  • Existing methods struggle with low-coverage data and require genotype imputation.

Purpose of the Study:

  • Introduce novel statistical methods for case-parent trio association studies using NGS read counts.
  • Incorporate low-coverage data without genotype classification or imputation.
  • Evaluate method performance and determine sample size requirements for NGS experimental designs.

Main Methods:

  • Developed a likelihood-based approach using a 15-component parametric mixture model.
  • Developed a model-free approach using non-parametric statistical methods on read count ratios.
  • Conducted simulation studies to assess type I error and power.
  • Derived non-centrality parameters for sample size and coverage calculations.

Main Results:

  • Tests using classified genotypes showed inflated type I error rates with low-coverage data.
  • Proposed methods using posterior probabilities outperformed classified genotype tests.
  • Likelihood-based approach generally showed higher power than the non-parametric approach.
  • Calculated sample sizes for adolescent idiopathic scoliosis (AIS) study example.

Conclusions:

  • The proposed statistical methods effectively handle low-coverage NGS data in case-parent trio studies.
  • Avoidance of genotype classification/imputation improves accuracy and power.
  • Likelihood-based approach is recommended for higher power in genetic association studies.
  • Provides practical sample size and coverage recommendations for experimental design.