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De novo Gene Signature Identification from Single-Cell RNA-Seq with Hierarchical Poisson Factorization

Hanna Mendes Levitin, Jinzhou Yuan, Yim Ling Cheng, Francisco J.R. Ruiz, Erin C. Bush, Jeffrey N. Bruce, Peter Canoll, Antonio Iavarone, Anna Lasorella, David M. Blei, Peter A. Sims
doi: https://doi.org/10.1101/367003
Hanna Mendes Levitin
1Department of Systems Biology, Columbia University Medical Center, New York, NY 10032
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Jinzhou Yuan
1Department of Systems Biology, Columbia University Medical Center, New York, NY 10032
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Yim Ling Cheng
1Department of Systems Biology, Columbia University Medical Center, New York, NY 10032
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Francisco J.R. Ruiz
2Department of Computer Science, Columbia University, New York, NY 10025
3Department of Engineering, University of Cambridge, Cambridge, UK, CB2 1PZ
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Erin C. Bush
1Department of Systems Biology, Columbia University Medical Center, New York, NY 10032
4Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY 10032
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Jeffrey N. Bruce
5Department of Neurological Surgery, Columbia University Medical Center, New York, NY 10032
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Peter Canoll
6Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032
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Antonio Iavarone
6Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032
7Institute for Cancer Genetics, Columbia University Medical Center, New York, NY 10032
8Department of Neurology, Columbia University Medical Center, New York, NY 10032
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Anna Lasorella
6Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY 10032
7Institute for Cancer Genetics, Columbia University Medical Center, New York, NY 10032
9Deparment of Pediatrics, Columbia University Medical Center, New York, NY 10032
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David M. Blei
2Department of Computer Science, Columbia University, New York, NY 10025
10Department of Statistics, Columbia University Medical Center, New York, NY 10032
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  • For correspondence: david.blei@columbia.edu pas2182@cumc.columbia.edu
Peter A. Sims
1Department of Systems Biology, Columbia University Medical Center, New York, NY 10032
4Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY 10032
11Department of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY 10032
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  • For correspondence: david.blei@columbia.edu pas2182@cumc.columbia.edu
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Abstract

Common approaches to gene signature discovery in single cell RNA-sequencing (scRNA-seq) depend upon predefined structures like clusters or pseudo-temporal order, require prior normalization, or do not account for the sparsity of single cell data. We present single cell Hierarchical Poisson Factorization (scHPF), a Bayesian factorization method that adapts Hierarchical Poisson Factorization [1] for de novo discovery of both continuous and discrete expression patterns from scRNA-seq. scHPF does not require prior normalization and captures statistical properties of single cell data better than other methods in benchmark datasets. Applied to scRNA-seq of the core and margin of a high-grade glioma, scHPF uncovers marked differences in the abundance of glioma subpopulations across tumor regions and subtle, regionally-associated expression biases within glioma subpopulations. scHFP revealed an expression signature that was spatially biased towards the glioma-infiltrated margins and associated with inferior survival in glioblastoma.

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Posted July 11, 2018.
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De novo Gene Signature Identification from Single-Cell RNA-Seq with Hierarchical Poisson Factorization
Hanna Mendes Levitin, Jinzhou Yuan, Yim Ling Cheng, Francisco J.R. Ruiz, Erin C. Bush, Jeffrey N. Bruce, Peter Canoll, Antonio Iavarone, Anna Lasorella, David M. Blei, Peter A. Sims
bioRxiv 367003; doi: https://doi.org/10.1101/367003
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De novo Gene Signature Identification from Single-Cell RNA-Seq with Hierarchical Poisson Factorization
Hanna Mendes Levitin, Jinzhou Yuan, Yim Ling Cheng, Francisco J.R. Ruiz, Erin C. Bush, Jeffrey N. Bruce, Peter Canoll, Antonio Iavarone, Anna Lasorella, David M. Blei, Peter A. Sims
bioRxiv 367003; doi: https://doi.org/10.1101/367003

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