__________________________________________________________________________________________________________________________________________________________

Tellipsoid (version 08.1)                                                                                                 


Paper. Keyur Desai,  J.R. Deller, Jr. and J. Justin McCormick.
Tellipsoid: Exploiting inter-gene correlation for improved detection of differential gene expression, submitted to Bioinformatics. preprint. [pdf]

What is it? Tellipsoid is  a powerful statistical algorithm for detecting differential gene expression. The basic idea is to exploit inter-gene correlation to share information across gene summary statistics, but while doing so we also make use of identifiability-- the fact that in most microarray data sets, a large proportion of genes can be identified a priori as non-differential on the bases of their t-statistics. We have just begun to understand the full implications of  this simple but very different approach. Combining correlation with identifiability is the key here.

What can it do? Current version supports two-sample microarray studies. However, the core Tellipsoid methodology is much general.
__________________________________________________________________________________________________________________________________________________________

SIMPLE-MAX  Simultaneous Inference of Microarrays based on the PrincipLe of Entropy MAXimization.
Paper. Keyur Desai,  J.R. Deller, Jr. and J. Justin McCormick. THE DISTRIBUTION OF THE NUMBER OF FALSE DISCOVERIES IN HIGHLY CORRELATED DNA MICROARRAY DATA, submitted to Annals of Applied Statistics. preprint. [pdf]

What is it?
SIMPLEMAX is a method to ascertain the correct null distribution to tail counts of z values in the presence of substantial inter-gene correlation. Our basic goal in the SIMPLEMAX paper is to extend the second-moment theory for the null z-value histogram in [Efron (2007) Correlation and Large-Scale Simultaneous Signifcance Testing. Journal of the American Statistical Association, 102(477):93--103, 2007]to include third-moment skewness corrections. Efron, in the same paper, noticed the limitations of the 2nd-moment theory in some test cases; this motivated the research behind SIMPLEMAX.

What can it do? Current version supports two-sample microarray studies. SIMPLEMAX takes a gene expression matrix, microarray labels, and a tail-area and estimates an entire distribution of the number of false discoveries falling in that tail-area.

MATLAB: simplemax.zip (I have been tied up with Tellipsoid project for a while but in near future I plan to provide a more user friedly version of simplemax.)
__________________________________________________________________________________________________________________________________________________________


back to Keyur Desai's home page