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Related Experiment Videos

AfterQC: automatic filtering, trimming, error removing and quality control for fastq data.

Shifu Chen1,2,3, Tanxiao Huang2, Yanqing Zhou2

  • 1Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xueyuan Road, Shenzhen, China.

BMC Bioinformatics
|April 1, 2017
PubMed
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AfterQC is a novel tool that profiles and corrects sequencing errors in high-accuracy applications. It automates quality control and data filtering, significantly reducing false-positive variants in sequencing data.

Area of Science:

  • Genomics and Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • High-accuracy sequencing data is crucial for clinical applications but is often compromised by sequencing errors.
  • Existing tools primarily focus on quality profiling, with limited capabilities for quantifying or correcting sequencing errors.
  • A need exists for automated tools that can handle quality control, error profiling, and data correction.

Purpose of the Study:

  • To develop AfterQC, a tool designed to profile, quantify, and correct sequencing errors.
  • To provide automated quality control and data filtering features for sequencing data.
  • To enhance the accuracy of sequencing data, particularly for pair-end sequencing.

Main Methods:

  • AfterQC analyzes overlapping paired-end sequences to detect and remove adapters.
Keywords:
BubbleData filteringNGSOverlap analysisQuality control

Related Experiment Videos

  • It implements a novel base correction function for overlapping regions.
  • The tool detects and visualizes sequencing bubbles, filters polyX, and performs K-MER based strand bias profiling.

    • Main Results:

    • AfterQC automatically filters reads, corrects errors, and generates interactive HTML reports.
    • It supports batch processing with multiprocess capabilities for efficient analysis.
    • Error profiling reveals a strong platform-dependent distribution of sequencing errors.

    Conclusions:

    • AfterQC integrates quality control, data filtering, error profiling, and base correction into a single automated workflow.
    • It effectively reduces sequencing errors in pair-end data, leading to cleaner outputs.
    • The tool aids in minimizing false-positive variants, especially for low-frequency somatic mutations, requiring minimal user configuration.