Correlation-sharing for detection of differential gene expression

Details Correlation-sharing for detection of differential gene expression Correlation-sharing for detection of differential gene expression

2006-08-02

arxiv.org/abs/math/0608061v1

Mathematics

Statistics Theory

Scientific paper

We propose a method for detecting differential gene expression that exploits the correlation between genes. Our proposal averages the univariate scores of each feature with the scores in correlation neighborhoods. In a number of real and simulated examples, the new method often exhibits lower false discovery rates than simple t-statistic thresholding. We also provide some analysis of the asymptotic behavior of our proposal. The general idea of correlation-sharing can be applied to other prediction problems involving a large number of correlated features. We give an example in protein mass spectrometry.

Affiliated with

Also associated with

No associations

Rating

Correlation-sharing for detection of differential gene expression does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Correlation-sharing for detection of differential gene expression, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Correlation-sharing for detection of differential gene expression will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-265099