do-cluster.R <input> <outdir> <project> [options]


scRNA-seq Dimension Reduction and Clustering

positional arguments:
  infile            input seurat object
  outdir            output result folder
  project           project name

flags:
  -h, --help        show this help message and exit

optional arguments:
  -n, --nfeatures   number of variable features[default: 2000]
  -m, --method      reduction method: pca, harmony or iNMF[default: pca]
  -d, --dims        dimensions, that is npcs for pca [default: 30]
  -r, --resolution  resolution of cluster [default: 0.8]
  -k, --kparam      k of knn in FindNeighbor[default:20]
  -p, --plot        features to plot on umap [default: c(nFeature_RNA,percent.mt,percent.rb)]

do-cluster.R examples/input.rds ~/tests/cluster test

cluster
├── pbmc.cluster.fs=2000.ds=pca.dims=30.reso=0.80.clusters.tsv    # cluster statistics
├── pbmc.cluster.fs=2000.ds=pca.dims=30.reso=0.80.pdf             # cluster figures
├── pbmc.cluster.fs=2000.ds=pca.dims=30.reso=0.80.rds             # cluster object