GSMA: an approach to identify robust global and test Gene Signatures using Meta-Analysis

Abstract

Recent advances in biomedical research have made massive amount of transcriptomic data available in public repositories from different sources. Due to the heterogeneity present in the individual experiments, identifying reproducible biomarkers for a given disease from multiple independent studies has become a major challenge. The widely used meta-analysis approaches, such as Fisher’s method, Stouffer’s method, minP and maxP, have at least two major limitations: (i) they are sensitive to outliers, and (ii) they perform only one statistical test for each individual study, and hence do not fully utilize the potential sample size to gain statistical power.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jul 22, 2019
Source ID
10.1093/bioinformatics/btz561

Entities

People

  • Adib Shafi
  • Azam Peyvandipour
  • Sorin Draghici
  • Tin C. Nguyen

Organizations

  • National Institutes of Health
  • National Science Foundation
  • United States Department of Defense
  • University of Nevada, Reno
  • Wayne State University

Tags

Readers

  • Oncology and Biomarker-Based Cancer Detection.
  • Regression Analysis.

Technology Areas

  • Biotechnology