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Genotype Refinement

Overview

Genotype refinement is a critical process in our pipeline aimed at enhancing the reliability of genotype calls by utilizing additional population data. This step applies statistical methods to refine genotype probabilities and filter variants based on genotype quality (GQ) scores.

Implementation

The 11_genotype_refinement.sh script uses tools from the Genome Analysis Toolkit (GATK) to refine genotypes based on a model that incorporates population-wide allele frequencies. The script is set up to process data efficiently across multiple chromosomes.

Script Description

Configured for substantial computational tasks:

  • Nodes: 1
  • Memory: 30G
  • CPUs per Task: 4
  • Time Limit: 96:00:00
  • Job Name: genotype_refine
  • Job Array: Designed to handle multiple chromosomal segments in one pass.

The script initiates by setting up the required computational environment, loading modules, and preparing directories for input and output.

Tools Used

  • GATK (v4.4.0.0): Utilizes CalculateGenotypePosteriors for refining genotype probabilities and VariantFiltration to apply quality filters to genotypes based on predefined thresholds.

Process Flow

  1. Input Preparation:
    • The script retrieves recalibrated VCF files from the VQSR step and checks their existence before proceeding.
  2. Refinement Execution:
    • CalculateGenotypePosteriors: This tool is used to adjust genotype likelihoods based on allele frequency data from large reference populations (e.g., gnomAD).
    • VariantFiltration: Applies a filter to flag genotypes with a GQ score less than 20, helping to ensure that only high-confidence genotypes are used in subsequent analyses.
  3. Outputs:
    • Generates two sets of VCF files:
      • A refined VCF file with updated genotype likelihoods.
      • A filtered VCF file that excludes genotypes below a quality threshold, ensuring the dataset’s integrity for further analysis.

Quality Assurance

The process includes comprehensive logging and condition checks to ensure accuracy and efficiency. Error handling mechanisms are in place to address any issues during file handling or processing, enhancing the robustness of the pipeline.

Conclusion

Genotype refinement is an essential step to ensure the high quality and reliability of variant calls in genomic studies. By integrating additional genomic data and applying rigorous quality control measures, this step helps in producing highly accurate genetic analyses.