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BatchQC: interactive software for evaluating sample and batch effects in genomic data.

Solaiappan Manimaran1,2, Heather Marie Selby3, Kwame Okrah4

  • 1Department of Biostatistics, Boston University, Boston, MA.

Bioinformatics (Oxford, England)
|August 20, 2016
PubMed
Summary
This summary is machine-generated.

BatchQC software identifies and corrects technical biases in genomic data from multiple batches. This tool helps ensure accurate downstream analysis by evaluating and adjusting for batch effects.

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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genomic and microarray samples are often processed in batches, introducing technical biases.
  • These biases can compromise the accuracy of downstream data analysis.
  • Existing batch adjustment tools lack guidance on necessity and application.

Purpose of the Study:

  • To introduce BatchQC, a software pipeline for evaluating and adjusting batch effects in genomic datasets.
  • To provide interactive visualizations and statistics for assessing batch effect impact.
  • To enable users to apply and evaluate existing adjustment tools.

Main Methods:

  • Development of the BatchQC software pipeline.
  • Integration of interactive visualizations and statistical measures.
  • Application of BatchQC to simulated and real genomic data.
  • Facilitation of the application and interactive evaluation of existing batch adjustment tools.

Main Results:

  • BatchQC effectively evaluates the impact of batch effects in genomic data.
  • The pipeline assists in determining the necessity and method of batch correction.
  • Interactive evaluation of adjustment tool benefits is enabled.
  • Demonstrated effectiveness on both simulated and real-world datasets.

Conclusions:

  • BatchQC is a valuable toolkit for addressing batch effects in '-omics' data.
  • It enhances the reliability of genomic data analysis by managing technical biases.
  • The software provides a user-friendly approach to batch effect assessment and correction.