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Single-cell RNAseq dataset to demonstrate the use of NicheNet directly on a Seurat object. The data came from "Medaglia et al. Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq, Science 2017". This data was generated via the NICHE-seq method to characterize immune cell composition in the T cell area of inguinal lymph nodes, both in steady-state and 72 hours after lymphocytic choriomeningitis virus (LCMV) infection. The Seurat objects contain the aggregated data after applying the Seurat alignment pipeline. seuratObj.rds: full dataset seuratObj_test.rds: dataset with reduced size (only highly variable genes and CD8 T cells and monocytes)
{"references": ["Medaglia et al. Spatial reconstruction of immune niches by combining photoactivatable reporters and scRNA-seq, Science 2017"]}
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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