Deconvolution of “big data” in cancer genomics: from pancancer level to single cells

M. Chepeleva; Y. Wang; A. Kakoichankava; A. Muller; Tony Kaoma; P. V. Nazarov

Deconvolution of “big data” in cancer genomics: from pancancer level to single cells

M. Chepeleva
, Y. Wang
, A. Kakoichankava
, A. Muller
, Tony Kaoma
, P. V. Nazarov

Multiomics Data Science

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

Abstract

Large genomics pan-cancer datasets that were made publically available in the last decade are now complemented with measurements at single cell level and may include up to a billion data points. Here we show how deconvolution method based on independent component analysis can process transcriptomes measured for bulk samples at pan-cancer level and for single-cell measurements from normal tissues and neoplasia

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	7-11
Number of pages	5
ISBN (Print)	978-985-566-942-6.
Publication status	Published - 9 Jul 2020

Keywords

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

Access to Document

https://elib.bsu.by/handle/123456789/248592

Cite this

Chepeleva, M., Wang, Y., Kakoichankava, A., Muller, A., Kaoma, T., & Nazarov, P. V. (2020). Deconvolution of “big data” in cancer genomics: from pancancer level to single cells. 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. 7-11). BSU. https://elib.bsu.by/handle/123456789/248592

@inproceedings{53583283c34543fda7b3e9b0aa9e8ea7,

title = "Deconvolution of “big data” in cancer genomics: from pancancer level to single cells",

abstract = "Large genomics pan-cancer datasets that were made publically available in the last decade are now complemented with measurements at single cell level and may include up to a billion data points. Here we show how deconvolution method based on independent component analysis can process transcriptomes measured for bulk samples at pan-cancer level and for single-cell measurements from normal tissues and neoplasia",

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

author = "M. Chepeleva and Y. Wang and A. Kakoichankava and A. Muller and Tony Kaoma 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.",

year = "2020",

month = jul,

day = "9",

language = "English",

isbn = "978-985-566-942-6.",

pages = "7--11",

editor = "V.A. Bishkek and V. Skakun",

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

publisher = "BSU",

}

Chepeleva, M, Wang, Y, Kakoichankava, A, Muller, A, Kaoma, T & Nazarov, PV 2020, Deconvolution of “big data” in cancer genomics: from pancancer level to single cells. 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. 7-11. <https://elib.bsu.by/handle/123456789/248592>

Deconvolution of “big data” in cancer genomics: from pancancer level to single cells. / Chepeleva, M.; Wang, Y.; Kakoichankava, A. 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. 7-11.

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

TY - GEN

T1 - Deconvolution of “big data” in cancer genomics: from pancancer level to single cells

AU - Chepeleva, M.

AU - Wang, Y.

AU - Kakoichankava, A.

AU - Muller, A.

AU - Kaoma, Tony

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.

PY - 2020/7/9

Y1 - 2020/7/9

N2 - Large genomics pan-cancer datasets that were made publically available in the last decade are now complemented with measurements at single cell level and may include up to a billion data points. Here we show how deconvolution method based on independent component analysis can process transcriptomes measured for bulk samples at pan-cancer level and for single-cell measurements from normal tissues and neoplasia

AB - Large genomics pan-cancer datasets that were made publically available in the last decade are now complemented with measurements at single cell level and may include up to a billion data points. Here we show how deconvolution method based on independent component analysis can process transcriptomes measured for bulk samples at pan-cancer level and for single-cell measurements from normal tissues and neoplasia

KW - transcriptomics; RNA-seq; independent component analysis; pan-cancer; single-cell

M3 - Conference contribution

SN - 978-985-566-942-6.

SP - 7

EP - 11

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

A2 - Bishkek, V.A.

A2 - Skakun, V.

PB - BSU

CY - Minsk

ER -

Deconvolution of “big data” in cancer genomics: from pancancer level to single cells

Abstract

Keywords

Access to Document

Fingerprint

Cite this