Identification of Potential MicroRNA Biomarkers by Meta-analysis

  • Hongmei Zhu
  • Siu-wai Leung
Part of the Methods in Molecular Biology book series (MIMB, volume 1762)


Meta-analysis statistically assesses the results (e.g., effect sizes) across independent studies that are conducted in accordance with similar protocols and objectives. Current genomic meta-analysis studies do not perform extensive re-analysis on raw data because full data access would not be commonplace, although the best practice of open research for sharing well-formed data have been actively advocated. This chapter describes a simple and easy-to-follow method for conducting meta-analysis of multiple studies without using raw data. Examples for meta-analysis of microRNAs (miRNAs) are provided to illustrate the method. MiRNAs are potential biomarkers for early diagnosis and epigenetic monitoring of diseases. A number of miRNAs have been identified to be differentially expressed, i.e., overexpressed or underexpressed, under diseased states but only a small fraction would be highly effective biomarkers or therapeutic targets of diseases. The meta-analysis method as described in this chapter aims to identify the miRNAs that are consistently found dysregulated across independent studies as biomarkers.

Key words

microRNA Noncoding RNAs Meta-analysis Quality assessment Biomarkers Differential expression Early diagnosis 

Supplementary material

421474_1_En_24_MOESM1_ESM.csv (1 kb)
Example dataset with dysregulated miRNAs


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Hongmei Zhu
    • 1
  • Siu-wai Leung
    • 1
    • 2
  1. 1.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical SciencesUniversity of MacauTaipaChina
  2. 2.School of InformaticsUniversity of EdinburghEdinburghUK

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