BBKNN network generation


ID: bbknn
Namespace: neighbors

Example commands

You can run the pipeline using nextflow run.

View help

You can use --help as a parameter to get an overview of the possible parameters.

nextflow run openpipelines-bio/openpipeline \
  -r 1.0.1 -latest \
  -main-script target/nextflow/neighbors/bbknn/ \

Run command

Example of params.yaml
# Arguments
input: # please fill in - example: "path/to/file"
modality: "rna"
obsm_input: "X_pca"
obs_batch: "batch"
# output: "$id.$key.output.h5mu"
# output_compression: "gzip"
uns_output: "neighbors"
obsp_distances: "distances"
obsp_connectivities: "connectivities"
n_neighbors_within_batch: 3
n_pcs: 50
# n_trim: 123

# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"
nextflow run openpipelines-bio/openpipeline \
  -r 1.0.1 -latest \
  -profile docker \
  -main-script target/nextflow/neighbors/bbknn/ \
  -params-file params.yaml

Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.

Argument group


Name Description Attributes
--input Input h5mu file file, required
--modality string, default: "rna"
--obsm_input The dimensionality reduction in .obsm to use for neighbour detection. Defaults to X_pca. string, default: "X_pca"
--obs_batch .obs column name discriminating between your batches. string, default: "batch"
--output Output .h5mu file. file, required, example: "output.h5mu"
--output_compression The compression format to be used on the output h5mu object. string, example: "gzip"
--uns_output Mandatory .uns slot to store various neighbor output objects. string, default: "neighbors"
--obsp_distances In which .obsp slot to store the distance matrix between the resulting neighbors. string, default: "distances"
--obsp_connectivities In which .obsp slot to store the connectivities matrix between the resulting neighbors. string, default: "connectivities"
--n_neighbors_within_batch How many top neighbours to report for each batch; total number of neighbours in the initial k-nearest-neighbours computation will be this number times the number of batches. integer, default: 3
--n_pcs How many dimensions (in case of PCA, principal components) to use in the analysis. integer, default: 50
--n_trim Trim the neighbours of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. The lower the value the more independent the individual populations, at the cost of more conserved batch effect. If None (default), sets the parameter value automatically to 10 times neighbors_within_batch times the number of batches. Set to 0 to skip. integer


  • Dries De Maeyer (author)

  • Dries Schaumont (maintainer)