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High-dimensional genomic data bias correction and data integration using MANCIE

High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on t...

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Autores principales: Zang, Chongzhi, Wang, Tao, Deng, Ke, Li, Bo, Hu, Sheng'en, Qin, Qian, Xiao, Tengfei, Zhang, Shihua, Meyer, Clifford A., He, Housheng Hansen, Brown, Myles, Liu, Jun S., Xie, Yang, Liu, X. Shirley
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833864/
https://www.ncbi.nlm.nih.gov/pubmed/27072482
http://dx.doi.org/10.1038/ncomms11305
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author Zang, Chongzhi
Wang, Tao
Deng, Ke
Li, Bo
Hu, Sheng'en
Qin, Qian
Xiao, Tengfei
Zhang, Shihua
Meyer, Clifford A.
He, Housheng Hansen
Brown, Myles
Liu, Jun S.
Xie, Yang
Liu, X. Shirley
author_facet Zang, Chongzhi
Wang, Tao
Deng, Ke
Li, Bo
Hu, Sheng'en
Qin, Qian
Xiao, Tengfei
Zhang, Shihua
Meyer, Clifford A.
He, Housheng Hansen
Brown, Myles
Liu, Jun S.
Xie, Yang
Liu, X. Shirley
author_sort Zang, Chongzhi
collection PubMed
description High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on the same samples. MANCIE uses a Bayesian-supported principal component analysis-based approach to adjust the data so as to achieve better consistency between sample-wise distances in the different profiles. MANCIE can improve tissue-specific clustering in ENCODE data, prognostic prediction in Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas data, copy number and expression agreement in Cancer Cell Line Encyclopedia data, and has broad applications in cross-platform, high-dimensional data integration.
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spelling pubmed-48338642016-05-02 High-dimensional genomic data bias correction and data integration using MANCIE Zang, Chongzhi Wang, Tao Deng, Ke Li, Bo Hu, Sheng'en Qin, Qian Xiao, Tengfei Zhang, Shihua Meyer, Clifford A. He, Housheng Hansen Brown, Myles Liu, Jun S. Xie, Yang Liu, X. Shirley Nat Commun Article High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on the same samples. MANCIE uses a Bayesian-supported principal component analysis-based approach to adjust the data so as to achieve better consistency between sample-wise distances in the different profiles. MANCIE can improve tissue-specific clustering in ENCODE data, prognostic prediction in Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas data, copy number and expression agreement in Cancer Cell Line Encyclopedia data, and has broad applications in cross-platform, high-dimensional data integration. Nature Publishing Group 2016-04-13 /pmc/articles/PMC4833864/ /pubmed/27072482 http://dx.doi.org/10.1038/ncomms11305 Text en Copyright © 2016, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Zang, Chongzhi
Wang, Tao
Deng, Ke
Li, Bo
Hu, Sheng'en
Qin, Qian
Xiao, Tengfei
Zhang, Shihua
Meyer, Clifford A.
He, Housheng Hansen
Brown, Myles
Liu, Jun S.
Xie, Yang
Liu, X. Shirley
High-dimensional genomic data bias correction and data integration using MANCIE
title High-dimensional genomic data bias correction and data integration using MANCIE
title_full High-dimensional genomic data bias correction and data integration using MANCIE
title_fullStr High-dimensional genomic data bias correction and data integration using MANCIE
title_full_unstemmed High-dimensional genomic data bias correction and data integration using MANCIE
title_short High-dimensional genomic data bias correction and data integration using MANCIE
title_sort high-dimensional genomic data bias correction and data integration using mancie
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4833864/
https://www.ncbi.nlm.nih.gov/pubmed/27072482
http://dx.doi.org/10.1038/ncomms11305
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