Bayesian joint estimation of CN and LOH aberrations

Paola M.V. Rancoita; Marcus Hutter; Francesco Bertoni; Ivo Kwee

doi:10.1007/978-3-642-02481-8_168

Bayesian joint estimation of CN and LOH aberrations

Paola M.V. Rancoita, Marcus Hutter, Francesco Bertoni, Ivo Kwee

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.

Original language	English
Title of host publication	Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings
Pages	1109-1117
Number of pages	9
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-02481-8_168
Publication status	Published - 2009
Event	10th International Work-Conference on Artificial Neural Networks, IWANN 2009 - Salamanca, Spain Duration: 10 Jun 2009 → 12 Jun 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	5518 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	10th International Work-Conference on Artificial Neural Networks, IWANN 2009
Country/Territory	Spain
City	Salamanca
Period	10/06/09 → 12/06/09

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10.1007/978-3-642-02481-8_168

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Rancoita, P. M. V., Hutter, M., Bertoni, F., & Kwee, I. (2009). Bayesian joint estimation of CN and LOH aberrations. In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings (PART 2 ed., pp. 1109-1117). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5518 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-02481-8_168

Rancoita, Paola M.V. ; Hutter, Marcus ; Bertoni, Francesco et al. / Bayesian joint estimation of CN and LOH aberrations. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2. ed. 2009. pp. 1109-1117 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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title = "Bayesian joint estimation of CN and LOH aberrations",

abstract = "SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.",

keywords = "Bayesian regression, Change point problem, DNA copy number estimation, LOH estimation, Piecewise constant function",

author = "Rancoita, {Paola M.V.} and Marcus Hutter and Francesco Bertoni and Ivo Kwee",

year = "2009",

doi = "10.1007/978-3-642-02481-8_168",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings",

edition = "PART 2",

note = "10th International Work-Conference on Artificial Neural Networks, IWANN 2009 ; Conference date: 10-06-2009 Through 12-06-2009",

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Rancoita, PMV, Hutter, M, Bertoni, F & Kwee, I 2009, Bayesian joint estimation of CN and LOH aberrations. in Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 5518 LNCS, pp. 1109-1117, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, Salamanca, Spain, 10/06/09. https://doi.org/10.1007/978-3-642-02481-8_168

Bayesian joint estimation of CN and LOH aberrations. / Rancoita, Paola M.V.; Hutter, Marcus; Bertoni, Francesco et al.
Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2. ed. 2009. p. 1109-1117 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5518 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Bayesian joint estimation of CN and LOH aberrations

AU - Rancoita, Paola M.V.

AU - Hutter, Marcus

AU - Bertoni, Francesco

AU - Kwee, Ivo

PY - 2009

Y1 - 2009

N2 - SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.

AB - SNP-microarrays are able to measure simultaneously both copy number and genotype at several single nucleotide polymorphism positions. Combining the two data, it is possible to better identify genomic aberrations. For this purpose, we propose a Bayesian piecewise constant regression which infers the type of aberration occurred, taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level. Namely, we model the distributions of the detected genotype given a specific genomic alteration and we estimate the hyper-parameters used on public reference datasets.

KW - Bayesian regression

KW - Change point problem

KW - DNA copy number estimation

KW - LOH estimation

KW - Piecewise constant function

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DO - 10.1007/978-3-642-02481-8_168

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SN - 3642024807

SN - 9783642024801

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings

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Rancoita PMV, Hutter M, Bertoni F, Kwee I. Bayesian joint estimation of CN and LOH aberrations. In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, Ambient Assisted Living - 10th Int. Work-Conf. Artificial Neural Networks, IWANN 2009 Workshops, Proceedings. PART 2 ed. 2009. p. 1109-1117. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-02481-8_168

Bayesian joint estimation of CN and LOH aberrations

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