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Sphinx: modeling transcriptional heterogeneity in single-cell RNA-Seq

View ORCID ProfileJinghua Gu, Qiumei Gu, Xuan Wang, Pingjian Yu, Wei Lin
doi: https://doi.org/10.1101/027870
Jinghua Gu
Baylor Institute for Immunology Research, Dallas, TX, USA
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Qiumei Gu
Baylor Institute for Immunology Research, Dallas, TX, USA
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Xuan Wang
Baylor Institute for Immunology Research, Dallas, TX, USA
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Pingjian Yu
Baylor Institute for Immunology Research, Dallas, TX, USA
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Wei Lin
Baylor Institute for Immunology Research, Dallas, TX, USA
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  • For correspondence: wei.lin@baylorhealth.edu
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Abstract

The significance of single-cell transcription resides not only in the cumulative expression strength of the cell population but also in its heterogeneity. We propose a new model that improves the detection of changes in the transcriptional heterogeneity pattern of RNA-Seq data using two heterogeneity parameters: ‘burst proportion’ and ‘burst magnitude’, whose changes are validated using RNA-FISH. Transcriptional ‘co-bursting’ – governed by distinct mechanisms during myoblast proliferation and differentiation – is described here.

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Posted October 01, 2015.
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Sphinx: modeling transcriptional heterogeneity in single-cell RNA-Seq
Jinghua Gu, Qiumei Gu, Xuan Wang, Pingjian Yu, Wei Lin
bioRxiv 027870; doi: https://doi.org/10.1101/027870
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Sphinx: modeling transcriptional heterogeneity in single-cell RNA-Seq
Jinghua Gu, Qiumei Gu, Xuan Wang, Pingjian Yu, Wei Lin
bioRxiv 027870; doi: https://doi.org/10.1101/027870

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