Journal
FEBS LETTERS
Volume 591, Issue 15, Pages 2213-2225Publisher
WILEY
DOI: 10.1002/1873-3468.12684
Keywords
single-cell analysis methods and tools; single-cell genomics
Funding
- Open Targets
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The recent developments in high-throughput single-cell RNA sequencing technology (scRNA-seq) have enabled the generation of vast amounts of transcriptomic data at cellular resolution. With these advances come new modes of data analysis, building on high-dimensional data mining techniques. Here, we consider biological questions for which scRNA-seq data is used, both at a cell and gene level, and describe tools available for these types of analyses. This is an exciting and rapidly evolving field, where clustering, pseudotime inference, branching inference and gene-level analyses are particularly informative areas of computational analysis.
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