Matching markers and unlabeled configurations in protein gels
Abstract
Unlabeled shape analysis is a rapidly emerging and challenging area of statistics. This has been driven by various novel applications in bioinformatics. We consider here the situation where two configurations are matched under various constraints, namely, the configurations have a subset of manually located "markers" with high probability of matching each other while a larger subset consists of unlabeled points. We consider a plausible model and give an implementation using the EM algorithm. The work is motivated by a real experiment of gels for renal cancer and our approach allows for the possibility of missing and misallocated markers. The methodology is successfully used to automatically locate and remove a grossly misallocated marker within the given data set.
Keywords
Cite
@article{arxiv.1209.6167,
title = {Matching markers and unlabeled configurations in protein gels},
author = {Kanti V. Mardia and Emma M. Petty and Charles C. Taylor},
journal= {arXiv preprint arXiv:1209.6167},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.1214/12-AOAS544 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)