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Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper

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Statistical Genomics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2629))

Abstract

Tissues are composed of diverse cell types and cellular states that organize into distinct ecosystems with specialized functions. EcoTyper is a collection of machine learning tools for the large-scale delineation of cellular ecosystems and their constituent cell states from bulk, single-cell, and spatially resolved gene expression data. In this chapter, we provide a primer on EcoTyper and demonstrate its use for the discovery and recovery of cell states and ecosystems from healthy and diseased tissue specimens.

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Acknowledgments

We would like to thank E. Brown for providing critical feedback on the manuscript. This work was supported by grants from the American Association for Cancer Research (C.B.S., 19-40-12-STEE), the National Cancer Institute (A.M.N., R01CA255450 and R00CA187192; A.J.G., U54CA209971 and U24CA224309; A.A.A., R01CA233975), the Stanford Bio-X Interdisciplinary Initiatives Seed Grants Program (IIP) (A.M.N.), the Donald E. and Delia B. Baxter Foundation (A.M.N.)., the Virginia and D.K. Ludwig Fund for Cancer Research (A.A.A., A.M.N.)., the Stinehart-Reed Foundation (A.A.A., A.M.N.), the Bakewell Foundation (A.A.A.), the SDW/DT and Shanahan Family Foundations (A.A.A.) and the Fund for Cancer Informatics (A.J.G.).

Author information

Authors and Affiliations

  1. Department of Biomedical Data Science, Stanford University, Stanford, CA, USA

    Chloé B. Steen, Bogdan A. Luca, Andrew J. Gentles & Aaron M. Newman

  2. Department of Medical Genetics, Oslo University Hospital, Oslo, Norway

    Chloé B. Steen

  3. Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA

    Chloé B. Steen & Ash A. Alizadeh

  4. Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, CA, USA

    Bogdan A. Luca & Andrew J. Gentles

  5. Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA

    Ash A. Alizadeh & Aaron M. Newman

  6. Division of Hematology, Department of Medicine, Stanford Cancer Institute, Stanford University, Stanford, CA, USA

    Ash A. Alizadeh

  7. Stanford Cancer Institute, Stanford University, Stanford, CA, USA

    Ash A. Alizadeh, Andrew J. Gentles & Aaron M. Newman

Authors
  1. Chloé B. Steen
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  2. Bogdan A. Luca
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  3. Ash A. Alizadeh
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  4. Andrew J. Gentles
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  5. Aaron M. Newman
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Corresponding author

Correspondence to Aaron M. Newman .

Editor information

Editors and Affiliations

  1. Moffitt Cancer Center, Tampa, FL, USA

    Brooke Fridley

  2. Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA

    Xuefeng Wang

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© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

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Steen, C.B., Luca, B.A., Alizadeh, A.A., Gentles, A.J., Newman, A.M. (2023). Profiling Cellular Ecosystems at Single-Cell Resolution and at Scale with EcoTyper. In: Fridley, B., Wang, X. (eds) Statistical Genomics. Methods in Molecular Biology, vol 2629. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2986-4_4

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  • DOI: https://doi.org/10.1007/978-1-0716-2986-4_4

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2985-7

  • Online ISBN: 978-1-0716-2986-4

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