links for 2009-07-10

In statistics, resampling is any of a variety of methods for doing one of the following: 1. Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping) 2. Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests) 3. Validating models by using random subsets (bootstrapping, cross validation) Common resampling techniques include bootstrapping, jackknifing and permutation tests.

Chromosomal translocations are common in cancer, and in some cases may be causal in the progression of the disease. Using microarrays, in which the expression of thousands of genes are simultaneously measured, could potentially allow one to detect recurrent translocations for a particular cancer type. Standard statistical tests, such as the t-test are not suited for detecting these translocations, but a simple test based on robust centering and scaling of the data to help detect outlier samples, followed by a search for pairs of samples with mutually exclusive outliers, may be used to find genes involved in recurrent translocations. We have implemented this method, termed Cancer Outlier Profile Analysis (COPA) in an R package (that we call the copa package), and show its applicability on a publicly available dataset. AVAILABILITY: http://www.bioconductor.org

# LEMMA is an R program that implements the RR model to analyze normalized microarray data. This version (1.1, 2009-05-27) supports two treatments and three-way classification: null genes, for which statistically there is no difference in expression between the two treatment groups; nonnull group #1 - genes that are significantly more expressed in group 1 than in group 2; and nonnull group #2 - genes that are significantly more expressed in group 2 than in group 1; or # two-way classification (null and nonnull genes, as in the LEMMA paper)