Too much data, but little inter-changeability: a lesson learned from mining public data on tissue specificity of gene expression
2006

Comparing Gene Expression Data from Different Technologies

Sample size: 7536 publication Evidence: moderate

Author Information

Author(s): Li Shuyu, Li Yiqun Helen, Wei Tao, Su Eric Wen, Duffin Kevin, Liao Birong

Primary Institution: Lilly Research Laboratories, Eli Lilly and Company

Hypothesis

Can gene expression data from SAGE and microarray technologies be compared effectively?

Conclusion

The study found significant discrepancies in tissue expression patterns between SAGE and microarray platforms, primarily due to mapping errors and differences in gene variants.

Supporting Evidence

  • 42-54% of genes showed significant correlations in tissue expression patterns between SAGE and GeneChip.
  • 30-40% of genes had positively correlated expression patterns.
  • 10-15% of genes had negatively correlated expression patterns.
  • The discrepancies were not likely due to tissue heterogeneity or microarray probe design.

Takeaway

This study looked at how genes behave in different tissues using two methods, and found that the results can be very different because of how the data is collected and analyzed.

Methodology

The study compared gene expression patterns from SAGE and microarray datasets using correlation coefficients and statistical tests.

Potential Biases

There may be biases due to the different biological samples used in SAGE and microarray technologies.

Limitations

The study is limited by the availability of data from public repositories and potential inaccuracies in gene mapping.

Statistical Information

P-Value

0.05

Statistical Significance

p=0.05

Digital Object Identifier (DOI)

10.1186/1745-6150-1-33

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