SeuratClustering¶

Cluster all cells or selected T/B cells selected by TOrBCellSelection.

If [TOrBCellSelection] is not set in the configuration, meaning all cells are T/B cells, this process will be run on all T/B cells. Otherwise, this process will be run on the selected T/B cells by TOrBCellSelection.

See also: SeuratClusteringOfAllCells.

Input¶

• srtobj: The seurat object loaded by SeuratPreparing

Output¶

• outfile: Default: {{in.srtobj | stem}}.qs.
  The seurat object with cluster information at seurat_clusters.
  

Environment Variables¶

• ncores (type=int;order=-100): Default: 1.
  Number of cores to use.
  Used in future::plan(strategy = "multicore", workers = <ncores>) to parallelize some Seurat procedures.
  See also: https://satijalab.org/seurat/articles/future_vignette.html
• RunUMAP (ns): Arguments for RunUMAP().
  object is specified internally, and - in the key will be replaced with ..
  dims=N will be expanded to dims=1:N; The maximal value of N will be the minimum of N and the number of columns - 1 for each sample.
  
  • dims (type=int): The number of PCs to use
  • reduction: The reduction to use for UMAP.
    If not provided, sobj@misc$integrated_new_reduction will be used.
    
  • <more>: See https://satijalab.org/seurat/reference/runumap
• RunPCA (ns): Arguments for RunPCA().
  
• FindNeighbors (ns): Arguments for FindNeighbors().
  object is specified internally, and - in the key will be replaced with ..
  
  • reduction: The reduction to use.
    If not provided, sobj@misc$integrated_new_reduction will be used.
    
  • <more>: See https://satijalab.org/seurat/reference/findneighbors
• FindClusters (ns): Arguments for FindClusters().
  object is specified internally, and - in the key will be replaced with ..
  The cluster labels will be saved in seurat_clusters and prefixed with "c".
  The first cluster will be "c1", instead of "c0".
  
  • resolution (type=auto): Default: 0.8.
    The resolution of the clustering. You can have multiple resolutions as a list or as a string separated by comma.
    Ranges are also supported, for example: 0.1:0.5:0.1 will generate 0.1, 0.2, 0.3, 0.4, 0.5. The step can be omitted, defaulting to 0.1.
    The results will be saved in seurat_clusters_<resolution>.
    The final resolution will be used to define the clusters at seurat_clusters.
    
  • <more>: See https://satijalab.org/seurat/reference/findclusters
• cache (type=auto): Default: /tmp.
  Where to cache the information at different steps.
  If True, the seurat object will be cached in the job output directory, which will be not cleaned up when job is rerunning.
  Set to False to not cache the results.
  

Metadata¶

The metadata of the Seurat object will be updated with the cluster assignments: