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An algorithm to segment count data using a binomial negative model

Rigaill, G (INRA-CNRS-Université d'Evry Val d'Essonne, URGV)
Thursday 16 January 2014, 10:00-10:30

Seminar Room 1, Newton Institute


We consider the problem of segmenting a count data profile. We developed an algorithm to recover the best (w.r.t the likelihood) segmentations in 1 to K_{max} segments. We prove that the optimal segmentation can be recovered using a compression scheme which reduces the time complexity. The compression is particularly efficient when the signal has large plateaus. We illustrate our algorithm on next generation sequencing data.


[pdf ]


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