Testing the hypothesis of tissue selectivity: the intersection-union test and a Bayesian approach Export

@article{citeulike:5445451, abstract = {Motivation: Finding genes that are preferentially expressed in a particular tissue or condition is a problem that cannot be solved by standard statistical testing procedures. A relatively unknown procedure that can be used is the intersection-union test (IUT). However, two disadvantages of the IUT are that it is conservative and it conveys only the information of the least differing target tissue-other tissue pair. Results: We propose a Bayesian procedure that quantifies how much evidence there is in the overall expression profile for selective over-expression. In a small simulation study, it is shown that the proposed method outperforms the IUT when it comes to finding selectively expressed genes. An application to publicly available data consisting of 22 tissues shows that the Bayesian method indeed selects genes with functions that reflect the specific tissue functions. The proposed method can also be used to find genes that are underexpressed in a particular tissue. Availability: Both MATLAB and R code that implement the IUT and the Bayesian procedure in an efficient way, can be downloaded at http://ppw.kuleuven.be/okp/software/BayesianIUT/. Contact: katrijn.vandeun@psy.kuleuven.be 10.1093/bioinformatics/btp439}, author = {Van Deun, K. and Hoijtink, H. and Thorrez, L. and Van Lommel, L. and Schuit, F. and Van Mechelen, I.}, citeulike-article-id = {5445451}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btp439}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/content/25/19/2588.abstract}, citeulike-linkout-2 = {http://bioinformatics.oxfordjournals.org/content/25/19/2588.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19671693}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19671693}, day = {1}, doi = {10.1093/bioinformatics/btp439}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {condition, differential, expression, intersection, multivariate, subset, tissue, union}, month = {October}, number = {19}, pages = {2588--2594}, posted-at = {2009-09-28 11:05:41}, priority = {2}, title = {Testing the hypothesis of tissue selectivity: the intersection-union test and a Bayesian approach}, url = {http://dx.doi.org/10.1093/bioinformatics/btp439}, volume = {25}, year = {2009} }

TY - JOUR ID - citeulike:5445451 L3 - citeulike-article-id:5445451 N2 - Motivation: Finding genes that are preferentially expressed in a particular tissue or condition is a problem that cannot be solved by standard statistical testing procedures. A relatively unknown procedure that can be used is the intersection-union test (IUT). However, two disadvantages of the IUT are that it is conservative and it conveys only the information of the least differing target tissue-other tissue pair. Results: We propose a Bayesian procedure that quantifies how much evidence there is in the overall expression profile for selective over-expression. In a small simulation study, it is shown that the proposed method outperforms the IUT when it comes to finding selectively expressed genes. An application to publicly available data consisting of 22 tissues shows that the Bayesian method indeed selects genes with functions that reflect the specific tissue functions. The proposed method can also be used to find genes that are underexpressed in a particular tissue. Availability: Both MATLAB and R code that implement the IUT and the Bayesian procedure in an efficient way, can be downloaded at http://ppw.kuleuven.be/okp/software/BayesianIUT/. Contact: katrijn.vandeun@psy.kuleuven.be 10.1093/bioinformatics/btp439 IS - 19 JF - Bioinformatics SN - 1460-2059 EP - 2594 TI - Testing the hypothesis of tissue selectivity: the intersection-union test and a Bayesian approach VL - 25 SP - 2588 KW - condition KW - differential KW - expression KW - intersection KW - multivariate KW - subset KW - tissue KW - union AU - Van Deun, K AU - Hoijtink, H AU - Thorrez, L AU - Van Lommel, L AU - Schuit, F AU - Van Mechelen, I PY - 2009/10/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btp439 ER -