Improved analysis of bacterial CGH data beyond the log-ratio paradigm Export

@article{citeulike:4195975, abstract = {BACKGROUND:Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach.RESULTS:A data set containing 32 hybridizations of sequenced versus sequenced genomes have been used to test and compare methods. A ROC-analysis has been performed to illustrate the ability to rank probes with respect to Present/Absent calls. Classification into Present and Absent is compared with that of a gaussian mixture model.CONCLUSIONS:The results indicate our proposed method is an improvement of existing methods with respect to ranking and classification of probes, especially for multi-genome arrays.}, author = {Snipen, Lars and Nyquist, Otto and Solheim, Margrete and Aakra, Agot and Nes, Ingolf}, citeulike-article-id = {4195975}, citeulike-linkout-0 = {http://dx.doi.org/10.1186/1471-2105-10-91}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/19298668}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=19298668}, doi = {10.1186/1471-2105-10-91}, issn = {1471-2105}, journal = {BMC Bioinformatics}, keywords = {microarray}, number = {1}, pages = {91+}, posted-at = {2009-03-19 19:18:56}, priority = {2}, title = {Improved analysis of bacterial CGH data beyond the log-ratio paradigm}, url = {http://dx.doi.org/10.1186/1471-2105-10-91}, volume = {10}, year = {2009} }

TY - JOUR ID - citeulike:4195975 L3 - citeulike-article-id:4195975 N2 - BACKGROUND:Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach.RESULTS:A data set containing 32 hybridizations of sequenced versus sequenced genomes have been used to test and compare methods. A ROC-analysis has been performed to illustrate the ability to rank probes with respect to Present/Absent calls. Classification into Present and Absent is compared with that of a gaussian mixture model.CONCLUSIONS:The results indicate our proposed method is an improvement of existing methods with respect to ranking and classification of probes, especially for multi-genome arrays. IS - 1 JF - BMC Bioinformatics SN - 1471-2105 TI - Improved analysis of bacterial CGH data beyond the log-ratio paradigm VL - 10 SP - 91 KW - microarray AU - Snipen, Lars AU - Nyquist, Otto AU - Solheim, Margrete AU - Aakra, Agot AU - Nes, Ingolf PY - 2009/// UR - http://dx.doi.org/10.1186/1471-2105-10-91 ER -