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2D Representation of Transcriptomes by t-SNE Exposes Relatedness between Human Tissues

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  • Erdogan Taskesen
  • Marcel J T Reinders

Abstract

The GTEx Consortium reported that hierarchical clustering of RNA profiles from 25 unique tissue types among 1641 individuals accurately distinguished the tissue types, but a multidimensional scaling failed to generate a 2D projection of the data that separates tissue-subtypes. In this study we show that a projection by t-Distributed Stochastic Neighbor Embedding is in line with the cluster analysis which allows a more detailed examination and visualization of human tissue relationships.

Suggested Citation

  • Erdogan Taskesen & Marcel J T Reinders, 2016. "2D Representation of Transcriptomes by t-SNE Exposes Relatedness between Human Tissues," PLOS ONE, Public Library of Science, vol. 11(2), pages 1-6, February.
    • Handle: RePEc:plo:pone00:0149853
    DOI: 10.1371/journal.pone.0149853
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    References listed on IDEAS

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    1. Emma Pierson & the GTEx Consortium & Daphne Koller & Alexis Battle & Sara Mostafavi, 2015. "Sharing and Specificity of Co-expression Networks across 35 Human Tissues," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-19, May.
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    Cited by:

    1. Adrià Fernández-Torras & Miquel Duran-Frigola & Martino Bertoni & Martina Locatelli & Patrick Aloy, 2022. "Integrating and formatting biomedical data as pre-calculated knowledge graph embeddings in the Bioteque," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    2. Tara N. Yankee & Sungryong Oh & Emma Wentworth Winchester & Andrea Wilderman & Kelsey Robinson & Tia Gordon & Jill A. Rosenfeld & Jennifer VanOudenhove & Daryl A. Scott & Elizabeth J. Leslie & Justin , 2023. "Integrative analysis of transcriptome dynamics during human craniofacial development identifies candidate disease genes," Nature Communications, Nature, vol. 14(1), pages 1-23, December.

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