Finding a most likely clone ordering from oligonucleotide hybridization data.
Using an extension of a statistical model given by E. Lander and M. Waterman, we define the a posteriori probability of a clone ordering based upon oligonucleotide hybridization data. We give algorithms for computing the likelihood of a clone ordering and for finding a clone ordering of maximum likelihood. The dynamic programming algorithm for computing likelihoods runs in time O(mnc), where m is the number of oligonucleotide probes, n is the number of clones, and c is the coverage of the clone library. We use the Expectation-Maximization technique to maximize likelihoods.
Biological Sciences Division, University of Chicago, Illinois 60637-5415.
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Newberg
D000465:Algorithms; D003001:Cloning, Molecular / Q000379:methods*; D004247:DNA / Q000235:genetics*; D008957:Models, Genetic; D008962:Models, Theoretical; D009693:Nucleic Acid Hybridization; D009838:Oligodeoxyribonucleotides; D011336:Probability
D009838:Oligodeoxyribonucleotides; D004247:DNA