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Related Experiment Videos

A family-based test for correlation between gene expression and trait values.

Peter Kraft1, Eric Schadt, Jason Aten

  • 1Department of Biostatistics, University of California at Los Angeles, Los Angeles, CA 90095-1772, USA. pkraft@ucla.edu

American Journal of Human Genetics
|April 11, 2003
PubMed
Summary

This study introduces a new method, the family expression association test (FEXAT), to accurately analyze gene expression and complex disease genetics in families. FEXAT improves upon standard tests by accounting for family structures, reducing false discoveries and identifying key biological correlations.

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Area of Science:

  • Genetics
  • Bioinformatics
  • Systems Biology

Background:

  • Microarray technology enables integrated analysis of clinical traits, genetic markers, and gene expression in family studies.
  • Standard association tests can yield misleading results when family structures are not considered in genetic analyses.
  • Dissecting complex disease genetics requires methods that properly account for familial correlations.

Purpose of the Study:

  • To develop and validate a novel statistical method for analyzing gene expression associations within family studies.
  • To address the limitations of standard association tests when applied to family-based gene expression data.
  • To identify biologically relevant gene expression correlations missed by conventional methods.

Main Methods:

  • Development of a stratified family expression association test (FEXAT) to account for within-family correlations.

Related Experiment Videos

  • Simulation studies to evaluate the performance of FEXAT compared to standard unstratified tests.
  • Application of FEXAT to gene expression data from lymphoblastoid cell lines in CEPH families.

    • Main Results:

    • The FEXAT demonstrated a lower estimated false-discovery rate than the standard Pearson's correlation coefficient test for within-family associations.
    • FEXAT identified significant, biologically plausible correlations between beta catenin and WNT-activation pathway genes.
    • Standard tests failed to detect these key correlations, highlighting the importance of accounting for family structure.

    Conclusions:

    • The FEXAT is a more reliable method for dissecting complex disease genetics using family-based gene expression data.
    • Accounting for family structure is crucial for accurate gene expression association studies.
    • FEXAT enhances the discovery of biologically relevant genetic associations in human complex diseases.