Skip to content

Apply BQSR Specifications

Process Details

  • Name: applyBSQRS
  • Process UUID: 8hObxx5vX8Jmqciruce8BXLKcbSDim
  • Process Group: gatk4

Overview

The Apply BQSR process performs Base Quality Score Recalibration (BQSR) using GATK4 to improve the accuracy of base quality scores in sequencing data. BQSR is a critical preprocessing step that corrects systematic errors in base quality scores assigned by sequencing machines, leading to more accurate variant calling and downstream analyses. This process performs BQSR in two passes, with the second pass generating a recalibration report for quality assessment.

This process is implemented in Bash, which invokes GATK4 tools for base quality score recalibration.

Key Functionality

  • Base Quality Score Recalibration: Applies previously computed recalibration tables to correct systematic errors in base quality scores
  • Post-recalibration Analysis: Performs a second BaseRecalibrator run to generate post-recalibration statistics
  • Quality Assessment: Produces recalibration tables that can be used to evaluate the effectiveness of the BQSR process

Input/Output Specification

Inputs

Required Inputs

  • VCFset

    • Description: Set of VCF files containing known variants used for base quality score recalibration
    • Format: VCF

  • genomeDict

    • Description: Reference genome dictionary file required by GATK tools
    • Format: DICT

  • run_parameters

    • Description: Runtime parameters and configuration settings for the BQSR process
    • Format: run_parameters

Outputs

  • outputFileTab

    • Description: Tabulated output files containing recalibration statistics and reports
    • Format: TAB

  • mapped_reads

    • Description: BAM files with recalibrated base quality scores applied to the aligned reads
    • Format: BAM

References & Resources

  • Tool Documentation: Contact the team for details on GATK4 ApplyBQSR and BaseRecalibrator tools
  • Related Papers: McKenna, A., et al. (2010). The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297-1303. DOI: 10.1101/gr.107524.110