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Mapinsights: deep exploration of quality issues and error profiles in high-throughput sequence data.

Subrata Das1, Nidhan K Biswas1, Analabha Basu1

  • 1National Institute of Biomedical Genomics, Kalyani, 741251, West Bengal, India.

Nucleic Acids Research
|June 28, 2023
PubMed
Summary

Mapinsights is a new toolkit for high-throughput sequencing (HTS) data quality control. It detects technical artifacts and improves the accuracy of genomic variant identification.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • High-throughput sequencing (HTS) enables rapid genomic variant detection at base-pair resolution.
  • Identifying technical artifacts in HTS data is crucial for distinguishing true variants from false positives.

Purpose of the Study:

  • To develop Mapinsights, a toolkit for advanced quality control (QC) of sequence alignment files.
  • To enhance the detection of sequencing artifacts and outliers in HTS data with greater resolution than existing methods.

Main Methods:

  • Mapinsights employs cluster analysis using novel and existing QC features from sequence alignments.
  • The toolkit analyzes technical errors related to sequencing cycles, chemistry, libraries, and platforms.
  • It also identifies anomalies associated with sequencing depth.

Main Results:

  • Mapinsights successfully identified various quality issues in community standard datasets.
  • A logistic regression model based on Mapinsights features demonstrated high accuracy in detecting low-confidence variant sites.
  • The toolkit provides quantitative estimates and probabilistic arguments for error and bias identification.

Conclusions:

  • Mapinsights offers a deeper resolution for detecting sequencing artifacts compared to current methods.
  • The toolkit aids in identifying errors, bias, and outlier samples, thereby improving variant call authenticity.
  • Mapinsights is a valuable tool for enhancing the reliability of HTS data analysis.