SeuratClusteringOfAllCells

Cluster all cells, including T cells/non-T cells and B cells/non-Bcells using Seurat.

This process will perform clustering on all cells using Seurat package.
The clusters will then be used to select T/B cells by TOrBCellSelection process.

Note

If all your cells are all T/B cells (TOrBCellSelection is not set in configuration), you should not use this process.
Instead, you should use SeuratClustering process for unsupervised clustering, or SeuratMap2Ref process for supervised clustering.

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.
  • RunPCA (ns): Arguments for RunPCA().
  • FindNeighbors (ns): Arguments for FindNeighbors().
    object is specified internally, and - in the key will be replaced with ..
  • 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.

SeeAlso