Consensus approach for detection of cancer somatic mutations

Katarzyna Sieradzka; Kinga Leszczorz; Mateusz Garbulowski; Andrzej Polanski

doi:10.1007/978-3-319-67792-7_17

Consensus approach for detection of cancer somatic mutations

Katarzyna Sieradzka
, Kinga Leszczorz
, Mateusz Garbulowski
, Andrzej Polanski

Department of Graphics, Computer Vision and Digital Systems (RAU/RAU6)

Silesian University of Technology
Uppsala University

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

Abstract

We present a consensus algorithm for detection of somatic mutations in cancer genomics data, based on integrating results of four published somatic mutation callers, MuTect2, MuSE, Varscan2 and Somatic Sniper. We generate consensus lists of cancer somatic mutations by using a simple voting mechanisms. Performances of cancer somatic mutations searching algorithms are verified by a quality index defined by the estimated proportion between driver and passenger mutations. We demonstrate, on the basis of three large NGS datasets from the TCGA database, that our consensus algorithm improves detection of cancer somatic mutations.

Original language	English
Title of host publication	Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017
Editors	Aleksandra Gruca, Tadeusz Czachorski, Katarzyna Harezlak, Stanislaw Kozielski, Agnieszka Piotrowska, Tadeusz Czachorski
Publisher	Springer Verlag
Pages	163-171
Number of pages	9
ISBN (Print)	9783319677910
DOIs	https://doi.org/10.1007/978-3-319-67792-7_17
Publication status	Published - 2018
Event	5th International Conference on Man-Machine Interactions, ICMMI 2017 - Krakow, Poland Duration: 3 Oct 2017 → 6 Oct 2017

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	659
ISSN (Print)	2194-5357

Conference

Conference	5th International Conference on Man-Machine Interactions, ICMMI 2017
Country/Territory	Poland
City	Krakow
Period	3/10/17 → 6/10/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Cancer genomics
Consensus methods
Somatic mutations

ASJC Scopus subject areas

Control and Systems Engineering
General Computer Science

Access to Document

10.1007/978-3-319-67792-7_17

Cite this

Sieradzka, K., Leszczorz, K., Garbulowski, M., & Polanski, A. (2018). Consensus approach for detection of cancer somatic mutations. In A. Gruca, T. Czachorski, K. Harezlak, S. Kozielski, A. Piotrowska, & T. Czachorski (Eds.), Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017 (pp. 163-171). (Advances in Intelligent Systems and Computing; Vol. 659). Springer Verlag. https://doi.org/10.1007/978-3-319-67792-7_17

Sieradzka, Katarzyna ; Leszczorz, Kinga ; Garbulowski, Mateusz et al. / Consensus approach for detection of cancer somatic mutations. Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017. editor / Aleksandra Gruca ; Tadeusz Czachorski ; Katarzyna Harezlak ; Stanislaw Kozielski ; Agnieszka Piotrowska ; Tadeusz Czachorski. Springer Verlag, 2018. pp. 163-171 (Advances in Intelligent Systems and Computing).

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title = "Consensus approach for detection of cancer somatic mutations",

abstract = "We present a consensus algorithm for detection of somatic mutations in cancer genomics data, based on integrating results of four published somatic mutation callers, MuTect2, MuSE, Varscan2 and Somatic Sniper. We generate consensus lists of cancer somatic mutations by using a simple voting mechanisms. Performances of cancer somatic mutations searching algorithms are verified by a quality index defined by the estimated proportion between driver and passenger mutations. We demonstrate, on the basis of three large NGS datasets from the TCGA database, that our consensus algorithm improves detection of cancer somatic mutations.",

keywords = "Cancer genomics, Consensus methods, Somatic mutations",

author = "Katarzyna Sieradzka and Kinga Leszczorz and Mateusz Garbulowski and Andrzej Polanski",

note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG.; 5th International Conference on Man-Machine Interactions, ICMMI 2017 ; Conference date: 03-10-2017 Through 06-10-2017",

year = "2018",

doi = "10.1007/978-3-319-67792-7\_17",

language = "English",

isbn = "9783319677910",

series = "Advances in Intelligent Systems and Computing",

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pages = "163--171",

editor = "Aleksandra Gruca and Tadeusz Czachorski and Katarzyna Harezlak and Stanislaw Kozielski and Agnieszka Piotrowska and Tadeusz Czachorski",

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}

Sieradzka, K, Leszczorz, K, Garbulowski, M & Polanski, A 2018, Consensus approach for detection of cancer somatic mutations. in A Gruca, T Czachorski, K Harezlak, S Kozielski, A Piotrowska & T Czachorski (eds), Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017. Advances in Intelligent Systems and Computing, vol. 659, Springer Verlag, pp. 163-171, 5th International Conference on Man-Machine Interactions, ICMMI 2017, Krakow, Poland, 3/10/17. https://doi.org/10.1007/978-3-319-67792-7_17

Consensus approach for detection of cancer somatic mutations. / Sieradzka, Katarzyna; Leszczorz, Kinga; Garbulowski, Mateusz et al.
Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017. ed. / Aleksandra Gruca; Tadeusz Czachorski; Katarzyna Harezlak; Stanislaw Kozielski; Agnieszka Piotrowska; Tadeusz Czachorski. Springer Verlag, 2018. p. 163-171 (Advances in Intelligent Systems and Computing; Vol. 659).

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

TY - GEN

T1 - Consensus approach for detection of cancer somatic mutations

AU - Sieradzka, Katarzyna

AU - Leszczorz, Kinga

AU - Garbulowski, Mateusz

AU - Polanski, Andrzej

PY - 2018

Y1 - 2018

N2 - We present a consensus algorithm for detection of somatic mutations in cancer genomics data, based on integrating results of four published somatic mutation callers, MuTect2, MuSE, Varscan2 and Somatic Sniper. We generate consensus lists of cancer somatic mutations by using a simple voting mechanisms. Performances of cancer somatic mutations searching algorithms are verified by a quality index defined by the estimated proportion between driver and passenger mutations. We demonstrate, on the basis of three large NGS datasets from the TCGA database, that our consensus algorithm improves detection of cancer somatic mutations.

AB - We present a consensus algorithm for detection of somatic mutations in cancer genomics data, based on integrating results of four published somatic mutation callers, MuTect2, MuSE, Varscan2 and Somatic Sniper. We generate consensus lists of cancer somatic mutations by using a simple voting mechanisms. Performances of cancer somatic mutations searching algorithms are verified by a quality index defined by the estimated proportion between driver and passenger mutations. We demonstrate, on the basis of three large NGS datasets from the TCGA database, that our consensus algorithm improves detection of cancer somatic mutations.

KW - Cancer genomics

KW - Consensus methods

KW - Somatic mutations

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M3 - Conference contribution

AN - SCOPUS:85030764922

SN - 9783319677910

T3 - Advances in Intelligent Systems and Computing

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BT - Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017

A2 - Gruca, Aleksandra

A2 - Czachorski, Tadeusz

A2 - Harezlak, Katarzyna

A2 - Kozielski, Stanislaw

A2 - Piotrowska, Agnieszka

A2 - Czachorski, Tadeusz

PB - Springer Verlag

T2 - 5th International Conference on Man-Machine Interactions, ICMMI 2017

Y2 - 3 October 2017 through 6 October 2017

ER -

Sieradzka K, Leszczorz K, Garbulowski M, Polanski A. Consensus approach for detection of cancer somatic mutations. In Gruca A, Czachorski T, Harezlak K, Kozielski S, Piotrowska A, Czachorski T, editors, Man-Machine Interactions 5 - 5th International Conference on Man-Machine Interactions, ICMMI 2017. Springer Verlag. 2018. p. 163-171. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-319-67792-7_17

Consensus approach for detection of cancer somatic mutations

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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