Journal
NATURE METHODS
Volume 16, Issue 2, Pages 163-+Publisher
NATURE RESEARCH
DOI: 10.1038/s41592-018-0303-9
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Funding
- NIH [R012017-0569]
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Single-cell RNA-seq makes it possible to characterize the transcriptomes of cell types across different conditions and to identify their transcriptional signatures via differential analysis. Our method detects changes in transcript dynamics and in overall gene abundance in large numbers of cells to determine differential expression. When applied to transcript compatibility counts obtained via pseudoalignment, our approach provides a quantification-free analysis of 3' single-cell RNA-seq that can identify previously undetectable marker genes.
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