Abstract
With the advance of high-throughput sequencing technology, it is possible to investigate many complex biological and ecological systems. The objective of Human Microbiome Project (HMP) is to explore the microbial diversity in our human body and to provide experimental and computational standards for subsequent similar studies. The first-stage HMP generated a lot of data for computational analysis and provided a challenge for integration and interpretation of various microbiome data. In this paper, we introduce a data integration method –Laplacian-regularized Joint Non-negative Matrix Factorization (LJ-NMF) for analyzing functional and phylogenetic profiles from HMP jointly. The experimental results indicate that the proposed method offers an efficient framework for microbiome data analysis.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abdi, H., Williams, L.J., Abdi, H., Williams, L.J.: Principal component analysis. Wiley Interdisciplinary Reviews: Computational Statistics 2(4), 433–459 (2010)
Abubucker, S., Segata, N., Goll, J., et al.: Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome. PLoS Comput. Biol. 8(6), e1002358 (2012)
Akata, Z., Thurau, C., Bauckhage, C.: Non-negative matrix factorization in multimodality data for segmentation and label prediction (2011)
Arumugam, M., Raes, J., Pelletier, E., et al.: Enterotypes of the human gut microbiome. Nature 473(7346), 174–180 (2011), PMID: 21508958
Brunet, J.-P., Tamayo, P., Golub, T.R., Mesirov, J.P.: Metagenes and molecular pattern discovery using matrix factorization. PNAS 101(12), 4164–4169 (2004), PMID: 15016911
Cai, D., He, X., Han, J., Huang, T.: Graph regularized nonnegative matrix factorization for data representation. IEEE Transactions on Pattern Analysis and Machine Intelligence 33(8), 1548–1560 (2011)
Cho, I., Blaser, M.J.: The human microbiome: at the interface of health and disease. Nature Reviews Genetics 13(4), 260–270 (2012)
The Human Microbiome Project Consortium: A framework for human microbiome research. Nature 486(7402), 215–221 (2012)
Eweiwi, A., Cheema, M.S., Bauckhage, C.: Discriminative joint non-negative matrix factorization for human action classification. In: Weickert, J., Hein, M., Schiele, B. (eds.) GCPR 2013. LNCS, vol. 8142, pp. 61–70. Springer, Heidelberg (2013)
Guillamet, D., Vitria, J.: Classifying Faces with Non-negative Matrix Factorization (2002)
Handelsman, J., Rondon, M.R., Brady, S.F., Clardy, J., Goodman, R.M.: Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. Chem. Biol. 5(10), R245–R249 (1998), PMID: 9818143
Jeffery, I.B., Claesson, M.J., O’Toole, P.W., Shanahan, F.: Categorization of the gut microbiota: enterotypes or gradients? Nat. Rev. Micro. 10(9), 591–592 (2012)
Jiang, X., Langille, M.G.I., Neches, R.Y., Elliot, M., Levin, S.A., Eisen, J.A., Weitz, J.S., Dushoff, J.: Functional biogeography of ocean microbes revealed through non-negative matrix factorization. PLoS ONE 7(9), e43866 (2012a)
Jiang, X., Weitz, J., Dushoff, J.: A non-negative matrix factorization framework for identifying modular patterns in metagenomic profile data. Journal of Mathematical Biology 64(4), 697–711 (2012b)
Koren, O., Knights, D., Gonzalez, A., Waldron, L., Segata, N., Knight, R., Huttenhower, C., Ley, R.E.: A guide to enterotypes across the human body: Meta-analysis of microbial community structures in human microbiome datasets. PLoS Comput. Biol. 9(1), e1002863 (2013)
Lohmann, G., Volz, K.G., Ullsperger, M.: Using non-negative matrix factorization for single-trial analysis of fMRI data. NeuroImage 37(4), 1148–1160 (2007)
Qin, J., Li, R., Raes, J.: A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464(7285), 59–65 (2010)
Rusch, D.B., Halpern, A.L., Sutton, G.: The sorcerer II global ocean sampling expedition: Northwest atlantic through eastern tropical pacific. PLoS Biology 5(3), e77 (2007)
Torgerson, W.S.: Multidimensional scaling: I. Theory and method. Psychometrika 17(4), 401–419 (1952)
Venter, J.C., Remington, K., Heidelberg, J.F., Halpern, A.L., Rusch, D., Eisen, J.A., Wu, D., Paulsen, I., Nelson, K.E., Nelson, W., et al.: Environmental genome shotgun sequencing of the sargasso sea. Science 304(5667), 66–74 (2004)
Wu, G.D., Chen, J., Hoffmann, C., et al.: Linking long-term dietary patterns with gut microbial enterotypes. Science 334(6052), 105–108 (2011)
Yooseph, S., Sutton, G., Rusch, D.B., et al.: The sorcerer II global ocean sampling expedition: Expanding the universe of protein families. PLoS Biology 5(3), e16 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Jiang, X., Hu, X., Xu, W. (2014). Joint Analysis of Functional and Phylogenetic Composition for Human Microbiome Data. In: Basu, M., Pan, Y., Wang, J. (eds) Bioinformatics Research and Applications. ISBRA 2014. Lecture Notes in Computer Science(), vol 8492. Springer, Cham. https://doi.org/10.1007/978-3-319-08171-7_31
Download citation
DOI: https://doi.org/10.1007/978-3-319-08171-7_31
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08170-0
Online ISBN: 978-3-319-08171-7
eBook Packages: Computer ScienceComputer Science (R0)