Cancer outlier detection based on likelihood ratio test Export

@article{citeulike:3376482, abstract = {Motivation: Microarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples. Results: We propose a likelihood-based approach which targets detecting the change of point in mean expression intensity in the group of cancer samples. A desirable property of the proposed approach is the availability of theoretical significance-level results. Simulation studies showed that the performance of the proposed approach is appealing in terms of both detection power and false discovery rate. And the real data example also favored the likelihood-based approach in terms of the biological relevance of the results. Availability: R code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/\~{}jhhu/cod-analysis/. Contact: jhu@mdanderson.org Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btn372}, author = {Hu, Jianhua}, citeulike-article-id = {3376482}, citeulike-linkout-0 = {http://dx.doi.org/10.1093/bioinformatics/btn372}, citeulike-linkout-1 = {http://bioinformatics.oxfordjournals.org/cgi/content/abstract/24/19/2193}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/18697774}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=18697774}, day = {1}, doi = {10.1093/bioinformatics/btn372}, journal = {Bioinformatics}, keywords = {copa, outlier}, month = {October}, number = {19}, pages = {2193--2199}, posted-at = {2008-11-24 16:20:00}, priority = {2}, title = {Cancer outlier detection based on likelihood ratio test}, url = {http://dx.doi.org/10.1093/bioinformatics/btn372}, volume = {24}, year = {2008} }

TY - JOUR ID - citeulike:3376482 L3 - citeulike-article-id:3376482 N2 - Motivation: Microarray experiments can be used to help study the role of chromosomal translocation in cancer development through cancer outlier detection. The aim is to identify genes that are up- or down-regulated in a subset of cancer samples in comparison to normal samples. Results: We propose a likelihood-based approach which targets detecting the change of point in mean expression intensity in the group of cancer samples. A desirable property of the proposed approach is the availability of theoretical significance-level results. Simulation studies showed that the performance of the proposed approach is appealing in terms of both detection power and false discovery rate. And the real data example also favored the likelihood-based approach in terms of the biological relevance of the results. Availability: R code to implement the proposed method in the statistical package R is available at: http://odin.mdacc.tmc.edu/~jhhu/cod-analysis/. Contact: jhu@mdanderson.org Supplementary information: Supplementary data are available at Bioinformatics online. 10.1093/bioinformatics/btn372 IS - 19 JF - Bioinformatics EP - 2199 TI - Cancer outlier detection based on likelihood ratio test VL - 24 SP - 2193 KW - copa KW - outlier AU - Hu, Jianhua PY - 2008/10/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btn372 ER -