RIRA is a multi-tissue single-cell RNAseq atlas from Rhesus macaque cells. It provides highly annotated reference data, and a number of pipelines to assign cell type to your data using RIRA's built-in models. Finally, it includes pipelines to replicate the process used to generate RIRA's reference labels, which might be useful for generating a similar reference for another species.
RIRA's data was generated and labeled using the following process:
- Merge data from XX 10x Genomics datasets, representing 8 tissues and XX rhesus macaques
- Perform strict QC and filtration, based on metrics such as per-cell RNA saturation
- For initial phenotyping, we used scGate with a set of rhesus-adapted gates to divide cells. This initial pass is lossy, and will not label all cells.
- Cells labeled by scGate were downsampled to equalize cells per class, and then fed as training data to celltypist. The resulting model (RIRA_Immune_v2) is available through this R package.
- The above model will classify cells into course bins (T/NK, Bcell, MoMacDC, and Other). For many analyses we find it useful to subdivide a dataset into these categories and then perform dimensionality reduction on these more homogenous subsets.
- RIRA provides a handful of models trained to identify more specific subsets (such as differentiating CD4 vs CD8 T cells)
# Use the built-in celltypist model to score cells according to course phenotypes (T/NK, Bcell, MoMacDC, Other):
seuratObj <- RIRA::RunCellTypist(seuratObj, modelName = ‘RIRA_Immune_v2’)
# Also the built-in celltypist model for finer scope T/NK lineage:
seuratObj <- RIRA::Classify_TNK(seuratObj)
# Make sure to update your Rprofile to include Bioconductor repos, such as adding this line to ~/.Rprofile:
local({options(repos = BiocManager::repositories())})
#Latest version:
devtools::install_github(repo = 'bimberlabinternal/RIRA', ref = 'master', dependencies = TRUE, upgrade = 'always')
Pre-packaged Docker images with all needed dependencies installed can be found on our GitHub Packages page. We recommend using a specific release, which you can do using tags:
docker pull ghcr.io/bimberlabinternal/rira:latest