wrappers/preprocessing/bbknn

Description

Compute a batch-balanced nearest-neighbor graph of observations, running
either the GPU (rapids-singlecell) or the CPU (bbknn) variant of
bbknn, selected with --device_type.

Inputs

Name	Type & Properties	Description
--input	file required	Input h5mu file.
--modality	string	Which modality from the input MuData file to process.
--obsm_input	string	Which .obsm slot to use as a starting embedding (use_rep).
--batch_key	string required	Which .obs column holds the batch assignment. Neighbors are searched within each batch separately and then merged.

Name

Type & Properties

--input

file

required

--modality

string

--obsm_input

string

--batch_key

string

required

Compute

Name	Type & Properties	Description
--device_type	string	Which implementation to run: the GPU (rapids-singlecell) variant or the CPU (scanpy/squidpy) variant of the component. Selecting `gpu` requires a CUDA-capable GPU; the component errors out if none is available (there is no automatic fallback to CPU).

Name

Type & Properties

--device_type

string

Outputs

Name	Type & Properties	Description
--output	file required output	Output h5mu file containing the found neighbors.
--uns_output	string	In which .uns slot to store the neighbor graph metadata.
--obsp_distances	string	In which .obsp slot to store the distance matrix between the resulting neighbors.
--obsp_connectivities	string	In which .obsp slot to store the connectivities matrix between the resulting neighbors.
--output_compression	string	Compression format to use for the output AnnData and/or Mudata objects. By default no compression is applied.

Name

Type & Properties

--output

file

required

output

--uns_output

string

--obsp_distances

string

--obsp_connectivities

string

--output_compression

string

Options

Name	Type & Properties	Description
--neighbors_within_batch	integer	How many top neighbors to report for each batch. Total number of neighbors per cell is this value times the number of batches.
--n_pcs	integer	Number of dimensions of the `--obsm_input` representation to use. If not set, all available dimensions are used.
--trim	integer	Trim the neighbors of each cell to these many top connectivities. May help with population independence and improve the tidiness of clustering. If not set, defaults to ten times the total number of neighbors per cell.

Name

Type & Properties

--neighbors_within_batch

integer

--n_pcs

integer

--trim

integer

rapids-singlecell options

Name	Type & Properties	Description
--overwrite	boolean	Allow overwriting the .uns/.obsp output slots if they already exist.
--metric	string	The distance metric to use.
--algorithm	string	The KNN query algorithm to use (provided by cuVS). See https://docs.rapids.ai/api/cuvs/stable/ for details.
--random_state	integer	A random seed.

Name

Type & Properties

--overwrite

boolean

--metric

string

--algorithm

string

--random_state

integer

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
modality: [ "rna" ]  
obsm_input: [ "X_pca" ]  
device_type: [ "gpu" ]  
output: "$id.$key.output.h5mu"  
uns_output: [ "neighbors" ]  
obsp_distances: [ "distances" ]  
obsp_connectivities: [ "connectivities" ]  
neighbors_within_batch: [ 3 ]  
overwrite: [ false ]  
metric: [ "euclidean" ]  
algorithm: [ "brute" ]  
random_state: [ 0 ]  
id: "run"  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/openpipeline_rapids.git \  
  -revision v0.1.3 \  
  -main-script target/nextflow/wrappers/preprocessing/bbknn/main.nf \  
  -params-file params.yaml

wrappers/preprocessing/bbknn

Inputs

Compute

Outputs

Options

rapids-singlecell options

Run this component

Relationships

Used by

Uses