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Statistical Comparison of Rank Lists and Molecular Profiles

技術優勢

Fast, sensitive, and quantitative determination of the degree of overlap between two genome-scale ranked gene lists. Surveys the whole range of gene-expression changes and thus avoids missing the point of maximal overlap signal, as can occur when using fixed thresholds. In a single visualization and with minimal data pre-processing, the RRHO map indicates which of several possible overlap trends is present in expression signature comparisons and the strength of the observed trend.

技術應用

Individuals interested in comparing genome-scale molecular data sets.

詳細技術說明

Comparing independent high-throughput gene-expression experiments can generate hypotheses about which gene-expression programs are shared between particular biological processes. Current techniques to compare expression profiles typically involve choosing a fixed differential expression threshold to summarize results, potentially reducing sensitivity to small but concordant changes. We have developed a threshold-free algorithm called Rank-rank Hypergeometric Overlap (RRHO). This algorithm steps through two gene lists ranked by the degree of differential expression observed in two profiling experiments, successively measuring the statistical significance of the number of overlapping genes. The output is a graphical map that shows the strength, pattern and bounds of correlation between two expression profiles. The threshold-free and graphical aspects of RRHO complement other rank-based approaches such as Gene Set Enrichment Analysis (GSEA), for which RRHO is a 2D analog. Rank-rank overlap analysis is a sensitive, robust and web-accessible method for detecting and visualizing overlap trends between two complete, continuous gene-expression profiles.

其他

State Of Development

This software may be licensed online for non-for-profit, academic research use at no charge.

Details on how to request a license online are available here.

For commercial use inquiries, please contact: innovation@research.ucla.edu.

Related Materials

Rank-rank hypergeometric overlap: identification of statistically significant overlap between gene-expression signatures. Nucleic Acids Research Volume 38, Issue 17:Pp. e169.

Additional Technologies by these Inventors

Tech ID/UC Case

23010/2011-035-0

Related Cases

2011-035-0