Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

M. Chepeleva; A. Kakoichankava; M. M. Yatskou; P. V. Nazarov

Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

M. Chepeleva, A. Kakoichankava, M. M. Yatskou, P. V. Nazarov

Multiomics Data Science

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

Abstract

Here we estimated the optimal parameters of the independent component analysis method regarding the tasks of identification of glioblastoma and pancreatic cancer subtypes, prediction of patient survival and characterization of active biological processes. Analysis of deconvolution results of bulk and single-cell data allows sharing annotation between highly correlated components and improving interpretability of the results

Original language	English
Title of host publication	Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020
Editors	V.A. Bishkek, V. Skakun
Place of Publication	Minsk
Publisher	BSU
Pages	170-173
Number of pages	4
ISBN (Print)	978-985-566-942-6.
Publication status	Published - 9 Jul 2020

Keywords

transcriptomics; RNA-seq; independent component analysis; single-cell; cancer; survival

Access to Document

https://elib.bsu.by/handle/123456789/248662

Cite this

Chepeleva, M., Kakoichankava, A., Yatskou, M. M., & Nazarov, P. V. (2020). Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability. In V. A. Bishkek, & V. Skakun (Eds.), Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020 (pp. 170-173). BSU. https://elib.bsu.by/handle/123456789/248662

Chepeleva, M. ; Kakoichankava, A. ; Yatskou, M. M. et al. / Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability. Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. editor / V.A. Bishkek ; V. Skakun. Minsk : BSU, 2020. pp. 170-173

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abstract = "Here we estimated the optimal parameters of the independent component analysis method regarding the tasks of identification of glioblastoma and pancreatic cancer subtypes, prediction of patient survival and characterization of active biological processes. Analysis of deconvolution results of bulk and single-cell data allows sharing annotation between highly correlated components and improving interpretability of the results",

keywords = "transcriptomics; RNA-seq; independent component analysis; single-cell; cancer; survival",

author = "M. Chepeleva and A. Kakoichankava and Yatskou, {M. M.} and Nazarov, {P. V.}",

note = "Proceedings paper Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. 2020 / Belarusian State University ; Editorial note : V. A., Bishkek. V. Skakun (ed.) [et al.]. - Minsk : BSU, 2020. - – 299 с. ISBN 978-985-566-942-6.",

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Chepeleva, M, Kakoichankava, A, Yatskou, MM & Nazarov, PV 2020, Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability. in VA Bishkek & V Skakun (eds), Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. BSU, Minsk, pp. 170-173. <https://elib.bsu.by/handle/123456789/248662>

Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability. / Chepeleva, M.; Kakoichankava, A.; Yatskou, M. M. et al.
Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. ed. / V.A. Bishkek; V. Skakun. Minsk: BSU, 2020. p. 170-173.

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

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T1 - Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

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AU - Kakoichankava, A.

AU - Yatskou, M. M.

AU - Nazarov, P. V.

N1 - Proceedings paper Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. 2020 / Belarusian State University ; Editorial note : V. A., Bishkek. V. Skakun (ed.) [et al.]. - Minsk : BSU, 2020. - – 299 с. ISBN 978-985-566-942-6.

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AB - Here we estimated the optimal parameters of the independent component analysis method regarding the tasks of identification of glioblastoma and pancreatic cancer subtypes, prediction of patient survival and characterization of active biological processes. Analysis of deconvolution results of bulk and single-cell data allows sharing annotation between highly correlated components and improving interpretability of the results

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BT - Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020

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Chepeleva M, Kakoichankava A, Yatskou MM, Nazarov PV. Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability. In Bishkek VA, Skakun V, editors, Computer Technologies and Data Analysis (CTDA'2020) : Materials of II International Scientific-Practical Conference, Minsk, 23-24 April, 2020. Minsk: BSU. 2020. p. 170-173

Independent component analysis of cancer transcriptomes: optimization of parameters and improvement of interpretability

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