De novo Gene Signature Identification from Single-Cell RNA-Seq with Hierarchical Poisson Factorization
| Main Authors: | Levitin, Hanna M., Yuan, Jinzhou, Cheng, Yim L., Ruiz, Francisco J. R., Bush, Erin C., Bruce, Jeffrey N., Canoll, Peter, Iavarone, Antonio, Lasorella, Anna, Blei, David M., Sims, Peter A. |
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| Format: | Article Journal |
| Bahasa: | eng |
| Terbitan: |
, 2020
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| Online Access: |
https://zenodo.org/record/3679343 |
Daftar Isi:
- 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 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 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.