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Matching markers and unlabeled configurations in protein gels. (English) Zbl 1401.92080

Summary: 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.

MSC:

92C40 Biochemistry, molecular biology
62P10 Applications of statistics to biology and medical sciences; meta analysis
92C50 Medical applications (general)

Software:

lp_solve; lpSolve
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References:

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