A New Estimator of Significance of Correlation in Time Series Data
Semyon Kruglyak Haixu Tang
Department of
Mathematics
University of Southern
California,
Los Angeles,
CA90089
(J. Comp. Biol., to be
published)
Many expression array
experiments monitor gene activity as an organism goes through some biological
process. It is desirable to find genes with similar expression patterns in the
resulting time series data.We propose a new simulation approach that assesses
the statistical significance of similarity scores between expression patterns.
The simulation takes into account the dependence between columns of data. Download fulltext paper
(gzipped ps format).