Integrative analysis of single-cell genomics data by coupled nonnegative matrix factorizations.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 29987051.
- Also identified by DOI 10.1073/pnas.1805681115 and PMC identifier 6065048.
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Abstract
When different types of functional genomics data are generated on single cells from different samples of cells from the same heterogeneous population, the clustering of cells in the different samples should be coupled. We formulate this "coupled clustering" problem as an optimization problem and propose the method of coupled nonnegative matrix factorizations (coupled NMF) for its solution. The method is illustrated by the integrative analysis of single-cell RNA-sequencing (RNA-seq) and single-cell ATAC-sequencing (ATAC-seq) data.
Medical subject headings
- Databases, Genetic
- Models, Genetic
- Sequence Analysis, RNA