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Big data to knowledge: common pitfalls in transcriptomics data analysis and representation.

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|August 7, 2019
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Summary

Omics technologies offer insights into human diseases, but translating big data into knowledge is challenging. A review of 91 transcriptomics datasets found common analysis and reporting flaws, suggesting improvements for gene expression data.

Keywords:
Big datadata analysisdifferentially expressed genequality controltranscriptomics

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Area of Science:

  • Genomics
  • Bioinformatics
  • Biostatistics

Background:

  • Omics technologies, particularly transcriptomics, offer a global perspective on human diseases.
  • The effective translation of large-scale omics data into actionable knowledge remains a significant hurdle in biomedical research.

Purpose of the Study:

  • To assess the quality of transcriptomics datasets and associated publications.
  • To identify common drawbacks in the analysis and reporting of transcriptomics studies.
  • To propose recommendations for improving gene expression data standards.

Main Methods:

  • Systematic quality control assessment of 91 transcriptomics datasets from the Gene Expression Omnibus (GEO) database.
  • Evaluation of the scientific publications derived from these selected datasets.
  • Analysis of identified drawbacks in data analysis and reporting practices.

Main Results:

  • Significant and frequent drawbacks were identified in the analysis and reporting of transcriptomics studies.
  • Quality issues were more prevalent than anticipated, potentially impacting the reliability of findings.
  • Inconsistencies in data generation, analysis, and reporting were observed across studies.

Conclusions:

  • There is a critical need to enhance the standards for gene expression data generation, analysis, and reporting.
  • Recommendations are provided for researchers and reviewers to improve the quality and reproducibility of transcriptomics research.
  • Addressing these drawbacks is essential for the reliable translation of omics data into biological insights and clinical applications.