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Identification of potential microRNA biomarkers by meta-analysis
Zhu H.2; Leung S.-W.2
AbstractMeta-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.
KeywordBiomarkers Differential expression Early diagnosis Meta-analysis microRNA Noncoding RNAs Quality assessment
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Document TypeBook
CollectionInstitute of Chinese Medical Sciences
Affiliation1.University of Edinburgh
2.Universidade de Macau
Recommended Citation
GB/T 7714
Zhu H.,Leung S.-W.. Identification of potential microRNA biomarkers by meta-analysis[M],2018.
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