While single cell RNA-seq (scRNA-seq) provides biological insights at the single cell resolution, dissociation of cells from tissues is required for this procedure, thereby destroying spatial context of cells and gene expression. Various methods have been devised to reconstruct the lost spatial context by integrating scRNA-seq data and an in situ atlas that has spatial information but for fewer landmark genes. This package is based on the method developed in the biorxiv paper Charting a tissue from single-cell transcriptomes by Nitzan et al., 2018 (https://doi.org/10.1101/456350), which uses optimal transport to reconstruct the spatial context with or without an in situ atlas. This method is called de novo Spatial Reconstruction (novoSpaRc), and is originally implemented in Python by the authors of the paper. This package is an R implementation of novoSpaRc.
|Bioconductor views||SingleCell Transcriptomics|
|Maintainer||Lambda Moses <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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