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Data pre-processing for analyzing microbiome data - A mini review.

Ruwen Zhou1, Siu Kin Ng1, Joseph Jao Yiu Sung1,2

  • 1Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, 308232, Singapore.

Computational and Structural Biotechnology Journal
|October 16, 2023
PubMed
Summary
This summary is machine-generated.

This review addresses the need for better preprocessing methods in human microbiome research. Standardized techniques are crucial for accurate analysis of microbial communities and reliable health impact studies.

Keywords:
16S rRNA SequencingBatch EffectData PreprocessingMicrobiome DataNormalization

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • The human microbiome significantly impacts health, making it a key research area.
  • High-throughput sequencing advances microbiome studies but faces analytical challenges.
  • Existing preprocessing methods lack standardization, hindering data quality and bias minimization.

Purpose of the Study:

  • To provide a comprehensive overview of preprocessing techniques for microbiome data.
  • To guide researchers in selecting appropriate methods for data analysis.
  • To identify areas requiring further methodological development in microbiome preprocessing.

Main Methods:

  • The review outlines a typical workflow for microbiome data analysis.
  • Key preprocessing steps discussed include quality filtering, batch effect correction, imputation, normalization, and data transformation.
  • Strengths and limitations of various techniques are highlighted.

Main Results:

  • A practical guide to microbiome data preprocessing is presented.
  • The review identifies critical areas for future methodological advancements.
  • Emphasis is placed on the importance of robust preprocessing for valid biological conclusions.

Conclusions:

  • Standardized and robust preprocessing is essential for accurate microbiome data analysis.
  • Improved preprocessing methods will enhance the reliability of findings on microbiome-health interactions.
  • Further research is needed to develop and validate advanced preprocessing techniques.