Unifying Probe Effect and Array Effect to Detect Transcribed Fragments in Tiling Arrays
In this paper, we present a model to elaborate the sources of randomness in multiple tiling array data. We also propose a new probe score system which integrate the intensity information of a probe and its neighbors. This new score system is obtained by using slide window and median polish strategies. These strategies.rstly unify probe affect across probes and the array effect across arrays based on the region-speci.c.xed values interpreting the transcription levels of regions in probes, then unite these uni.ed information into the region-speci.c.xed values. And this united information become a new standard to evaluate that probes are or aren抰 in transcriptional regions. Similar to median method, our method is a way that integrate the information from multiple arrays in the analysis stage rather than the results stage. A classical hidden Markov model (HMM) is used to model the distribution of tilling array probe scores in transcribed and non-transcribed regions and then to predict the transcribed fragments. The priority of the proposed score system is illustrated based on Affymetrix抯 RNA tiling array data.
GAO Qinghui JIA Yingmin CHENG Changfang YU Fashan
The Seventh Research Division and the Department of Systems and Control, Beihang University (BUAA), The Seventh Research Division and the Department of Systems and Control, Beihang University (BUAA), School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo 454000, Henan
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-5
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）