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Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular Patterns
Chen, Jinyu1,2; Zhang, Shihua1,2,3
AbstractThe increasing availability of high-throughput biological data, especially multi-dimensional genomic data across the same samples, has created an urgent need for modular and integrative analysis tools that can reveal the relationships among different layers of cellular activities. To this end, we present a MATLAB package, Matrix Integration Analysis (MIA), implementing and extending four published methods, designed based on two classical techniques, non-negative matrix factorization (NMF), and partial least squares (PLS). This package can integrate diverse types of genomic data (e.g., copy number variation, DNA methylation, gene expression, microRNA expression profiles, and/or gene network data) to identify the underlying modular patterns by each method. Particularly, we demonstrate the differences between these two classes of methods, which give users some suggestions about how to select a suitable method in the MIA package. MIA is a flexible tool which could handle a wide range of biological problems and data types. Besides, we also provide an executable version for users without a MATLAB license.
Keywordbioinformatics multi-dimensional genomics matrix integrative analysis data integration module discovery non-negative matrix factorization (NMF) partial least squares (PLS)
Funding ProjectNational Natural Science Foundation of China[11131009] ; National Natural Science Foundation of China[61379092] ; National Natural Science Foundation of China[61422309] ; National Natural Science Foundation of China[61621003] ; Strategic Priority Research Program of the Chinese Academy of Sciences (CAS)[XDB13040600] ; Chinese Academy of Sciences[KFZD-SW-219] ; National Key Research and Development Program of China[2017YFC0908405] ; CAS Frontier Science Research Key Project for Top Young Scientist[QYZDB-SSW-SYS008]
WOS Research AreaGenetics & Heredity
WOS SubjectGenetics & Heredity
WOS IDWOS:000433387900001
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Document Type期刊论文
Corresponding AuthorZhang, Shihua
Affiliation1.Chinese Acad Sci, Acad Math & Syst Sci, RCSDS, NCMIS,CEMS, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Anim Evolut & Genet, Kunming, Yunnan, Peoples R China
Recommended Citation
GB/T 7714
Chen, Jinyu,Zhang, Shihua. Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular Patterns[J]. FRONTIERS IN GENETICS,2018,9:12.
APA Chen, Jinyu,&Zhang, Shihua.(2018).Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular Patterns.FRONTIERS IN GENETICS,9,12.
MLA Chen, Jinyu,et al."Matrix Integrative Analysis (MIA) of Multiple Genomic Data for Modular Patterns".FRONTIERS IN GENETICS 9(2018):12.
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