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Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues

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Transcriptome Data Analysis

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1751))

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Abstract

Tissue heterogeneity is both a major confounding factor and an underexploited information source. While a handful of reports have demonstrated the potential of supervised methods to deconvolve tissue heterogeneity, these approaches require a priori information on the marker genes or composition of known subpopulations. To address the critical problem of the absence of validated marker genes for many (including novel) subpopulations, we develop a novel unsupervised deconvolution method, Convex Analysis of Mixtures (CAM), within a well-grounded mathematical framework, to dissect mixed gene expressions in heterogeneous tissue samples. To facilitate the utility of this method, we implement an R-Java CAM package that provides comprehensive analytic functions and graphic user interface (GUI).

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Arlington, VA, USA

    Niya Wang, Lulu Chen & Yue Wang

Authors
  1. Niya Wang
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  2. Lulu Chen
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  3. Yue Wang
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Corresponding author

Correspondence to Niya Wang .

Editor information

Editors and Affiliations

  1. Department of Cell Biology and Genetics, School of Basic Medicine, Shenzhen University Health, Science Center, Shenzhen, China

    Yejun Wang

  2. Epigenomics and Computational Biology Lab, Biocomplexity Institute of Virginia Tech, Blacksburg, Virginia, USA

    Ming-an Sun

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Wang, N., Chen, L., Wang, Y. (2018). Mathematical Modeling and Deconvolution of Molecular Heterogeneity Identifies Novel Subpopulations in Complex Tissues. In: Wang, Y., Sun, Ma. (eds) Transcriptome Data Analysis. Methods in Molecular Biology, vol 1751. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7710-9_16

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  • DOI: https://doi.org/10.1007/978-1-4939-7710-9_16

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7709-3

  • Online ISBN: 978-1-4939-7710-9

  • eBook Packages: Springer Protocols

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