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High-dimensional genomic data bias correction and data integration using MANCIE
Zang, Chongzhi1,2,3; Wang, Tao4,5; Deng, Ke6; Li, Bo1,2,3,7; Hu, Sheng'en8; Qin, Qian8; Xiao, Tengfei1,2,3,9,10; Zhang, Shihua11; Meyer, Clifford A.1,2,3; He, Housheng Hansen1,2,3,9,10,12; Brown, Myles3,9,10; Liu, Jun S.7; Xie, Yang4,13,14; Liu, X. Shirley1,2,3
2016-04-01
Source PublicationNATURE COMMUNICATIONS
ISSN2041-1723
Volume7Pages:8
AbstractHigh-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.
DOI10.1038/ncomms11305
Language英语
Funding ProjectUS National Institutes of Health (NIH)[U41HG7000] ; US National Institutes of Health (NIH)[1R01GM099409] ; US National Institutes of Health (NIH)[5R01CA172211] ; US National Institutes of Health (NIH)[1R01CA152301] ; National Natural Science Foundation of China (NSFC)[11401338] ; National Natural Science Foundation of China (NSFC)[61422309] ; Leukemia and Lymphoma Society (LLS)
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000374062000001
PublisherNATURE PUBLISHING GROUP
Citation statistics
Cited Times:13[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/22514
Collection应用数学研究所
Affiliation1.Dana Farber Canc Inst, Dept Biostat & Computat Biol, Boston, MA 02215 USA
2.Harvard Univ, TH Chan Sch Publ Hlth, Boston, MA 02215 USA
3.Dana Farber Canc Inst, Ctr Funct Canc Epigenet, Boston, MA 02215 USA
4.Univ Texas SW Med Ctr Dallas, Dept Clin Sci, Quantitat Biomed Res Ctr, Dallas, TX 75390 USA
5.Univ Texas SW Med Ctr Dallas, Ctr Genet Host Def, Dallas, TX 75390 USA
6.Tsinghua Univ, Ctr Stat Sci, Beijing 100084, Peoples R China
7.Harvard Univ, Dept Stat, Cambridge, MA 02138 USA
8.Tongji Univ, Sch Life Sci, Dept Bioinformat, Shanghai 200092, Peoples R China
9.Dana Farber Canc Inst, Dept Med Oncol, Boston, MA 02215 USA
10.Harvard Univ, Sch Med, Boston, MA 02215 USA
11.Chinese Acad Sci, Acad Math & Syst Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China
12.Univ Toronto, Dept Med Biophys, Toronto, ON M5G 1L7, Canada
13.Univ Texas SW Med Ctr Dallas, Dept Bioinformat, Dallas, TX 75390 USA
14.Univ Texas SW Med Ctr Dallas, Simons Comprehens Canc Ctr, Dallas, TX 75390 USA
Recommended Citation
GB/T 7714
Zang, Chongzhi,Wang, Tao,Deng, Ke,et al. High-dimensional genomic data bias correction and data integration using MANCIE[J]. NATURE COMMUNICATIONS,2016,7:8.
APA Zang, Chongzhi.,Wang, Tao.,Deng, Ke.,Li, Bo.,Hu, Sheng'en.,...&Liu, X. Shirley.(2016).High-dimensional genomic data bias correction and data integration using MANCIE.NATURE COMMUNICATIONS,7,8.
MLA Zang, Chongzhi,et al."High-dimensional genomic data bias correction and data integration using MANCIE".NATURE COMMUNICATIONS 7(2016):8.
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