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An optimal method to segment piecewise Poisson distributed signals with application to sequencing data

Abstract : To analyze the next generation sequencing data, the so-called read depth signal is often segmented with standard segmentation tools. However, these tools usually assume the signal to be a piecewise constant signal and contaminated with zero mean Gaussian noise, and therefore modeling error occurs. This paper models the read depth signal with piecewise Poisson distribution, which is more appropriate to the next generation sequencing mechanism. Based on the proposed model, an optimal dynamic programming algorithm with parallel computing is proposed to segment the piecewise signal, and furthermore detect the copy number variation.
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https://hal.archives-ouvertes.fr/hal-01163895
Contributor : Charles Soussen Connect in order to contact the contributor
Submitted on : Monday, June 15, 2015 - 5:08:06 PM
Last modification on : Wednesday, April 27, 2022 - 4:22:08 AM

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Junbo Duan, Charles Soussen, David Brie, Jérôme Idier, Yu-Ping Wang, et al.. An optimal method to segment piecewise Poisson distributed signals with application to sequencing data. 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015, Aug 2015, Milan, Italy. pp.6465-6468, ⟨10.1109/EMBC.2015.7319873⟩. ⟨hal-01163895⟩

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