ACM Computing Surveys (CSUR)
Computational Biology and Chemistry
Tri-mean-based statistical differential gene expression detection
International Journal of Data Mining and Bioinformatics
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
| Hi-index | 3.84 |
Summary: 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 Contact: jmacdon@med.umich.edu