Single cell RNA sequencing (scRNAseq) has made it possible to examine the cellular heterogeny within a tissue or sample, and observe changes and characteristics in specific cell types. To do this, we need to group the cells into clusters and figure out what they are.
The celaref (cell labelling by reference) package aims to streamline the cell-type identification step, by suggesting cluster labels on the basis of similarity to an already-characterised reference dataset - wheather that's from a similar experiment performed previously in the same lab, or from a public dataset from a similar sample.
To look for cluster similarities celaref needs:
The query dataset :
A reference dataset:
Query Group | Short Label | pval | ------------|------------------------------------|---------| cluster_1 |cluster_1:astrocytes_ependymal |2.98e-23 | cluster_2 |cluster_2:endothelial-mural |8.44e-10 | cluster_3 |cluster_3:no_similarity |NA | cluster_4 |cluster_4:microglia |2.71e-19 | cluster_5 |cluster_5:pyramidal SS\|interneurons|3.49e-10 | cluster_6 |cluster_6:oligodendrocytes |2.15e-28 |
This is a comparison of brain scRNAseq data from :
Full details in the vignette html - method description, manual and example analyses.
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