Nature MethodsBioinformaticsPeer-reviewed journal article
User-friendly, scalable tools and workflows for single-cell analysis
Pablo A MorenoiD, Ni HuangiD, Jonathan R. ManningiD, Suhaib MohammediD, Andrey Solovyev, Krzysztof PolańskiiD, Wendi BaconiD, Ruben Chazarra, Carlos N. Talavera-LópeziD, Maria DoyleiD, Guilhem Marnier, Björn Andreas GrüningiD, Helena RascheiD, Nancy GeorgeiD, Silvie Korena FexovaiD, Mohamed AlibiiD, Zhichao MiaoiD, Yasset Pérez‐RiveroliD, Maximilian HaeussleriD, Alvis BrāzmaiD, Sarah Amalia TeichmanniD, Kerstin B. MeyeriD, Irene PapatheodorouiD
Abstract
Single-cell RNA-Seq (scRNA-Seq) data analysis requires expertise in command-line tools, programming languages and scaling on compute infrastructure. As scRNA-Seq becomes widespread, computational pipelines need to be more accessible, simpler and scalable. We introduce an interactive analysis environment for scRNA-Seq, based on Galaxy, with ~70 functions from major single-cell analysis tools, which can be run on compute clusters, cloud providers or single machines, to bring compute to the data in scRNA-Seq.
- Citations
- 54
- FWCI
- 2.82
- Field percentile
- top 7%
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