期刊
BMC BIOINFORMATICS
卷 10, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1471-2105-10-91
关键词
-
类别
资金
- Norwegian University of Life Sciences
- European Union
- Research Council of Norway
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. Conclusion: 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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据