Corpus ID: 16390249

Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data

@article{Prabhakaran2016DirichletPM,
  title={Dirichlet Process Mixture Model for Correcting Technical Variation in Single-Cell Gene Expression Data},
  author={Sandhya Prabhakaran and E. Azizi and Ambrose Carr and D. Pe’er},
  journal={JMLR workshop and conference proceedings},
  year={2016},
  volume={48},
  pages={
          1070-1079
        }
}
We introduce an iterative normalization and clustering method for single-cell gene expression data. The emerging technology of single-cell RNA-seq gives access to gene expression measurements for thousands of cells, allowing discovery and characterization of cell types. However, the data is confounded by technical variation emanating from experimental errors and cell type-specific biases. Current approaches perform a global normalization prior to analyzing biological signals, which does not… Expand
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