Abstract
Motivation: Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instancewhen data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimationof the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed.Results: We present a computationally efficient method to obtain estimates of the number and location of the change points. Themethod is based on a simple transformation of data and it provides results quite robust to model misspecifications. The efficiency of the method guarantees moderate computational times regardless of theseries length and the number of change points.Availability: The methods described in this article are implemented in the new R package cumSeg available from the Comprehensive RArchive Network at http://CRAN.R-project.org/package=cumSeg.
Lingua originale | English |
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pagine (da-a) | 161-166 |
Numero di pagine | 6 |
Rivista | Bioinformatics |
Volume | 27 |
Stato di pubblicazione | Published - 2011 |
All Science Journal Classification (ASJC) codes
- ???subjectarea.asjc.2600.2613???
- ???subjectarea.asjc.1300.1303???
- ???subjectarea.asjc.1300.1312???
- ???subjectarea.asjc.1700.1706???
- ???subjectarea.asjc.1700.1703???
- ???subjectarea.asjc.2600.2605???