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Related Concept Videos

RNA-seq03:21

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Related Experiment Video

Updated: Apr 3, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
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An Application of Sequential Meta-Analysis to Gene Expression Studies.

Putri W Novianti1, Ingeborg van der Tweel1, Victor L Jong2

  • 1Biostatistics and Research Support, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands.

Cancer Informatics
|September 25, 2015
PubMed
Summary

Sequential meta-analysis (SMA) identified 313 differentially expressed genes in acute myeloid leukemia using seven gene expression datasets. This method evaluates cumulative evidence, determining if more experiments are needed for robust gene signatures.

Keywords:
differentially expressed genesgene expressionsequential meta-analysistriangular test

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Area of Science:

  • Genomics
  • Bioinformatics
  • Cancer Research

Background:

  • Gene expression studies often identify disease-specific gene subsets.
  • Meta-analysis of gene expression datasets can yield more reliable results.
  • Sequential meta-analysis (SMA) combines studies chronologically, controlling Type I error and pre-specifying statistical power.

Purpose of the Study:

  • To apply SMA for identifying gene expression signatures in acute myeloid leukemia (AML).
  • To evaluate the adequacy of cumulative evidence from multiple AML gene expression experiments.

Main Methods:

  • Utilized sequential meta-analysis (SMA) on seven raw gene expression datasets for AML.
  • Assessed cumulative sample information to determine statistical significance and power.

Main Results:

  • Identified 313 differentially expressed genes in AML based on cumulative experimental data.
  • Demonstrated SMA's capability to evaluate the sufficiency of evidence for gene discovery.

Conclusions:

  • SMA provides an alternative approach for gene list generation in complex diseases like AML.
  • The study highlights SMA's utility in assessing the need for further experiments in gene expression research.