wrappers/tools/leiden

Description

Cluster cells using the Leiden algorithm, running either the GPU
(rapids-singlecell) or the CPU (scanpy) variant of leiden, selected
with --device_type. Requires a precomputed neighbor graph.

Inputs

Name	Type & Properties	Description
--input	file required	Input h5mu file.
--modality	string	Which modality from the input MuData file to process.
--obsp_connectivities	string	In which .obsp slot the neighbor connectivities can be found.

Name

Type & Properties

--input

file

required

--modality

string

--obsp_connectivities

string

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.
--obsm_name	string	Name of the .obsm key under which to add the cluster labels. The name of the columns in the matrix will correspond to the resolutions.
--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

--obsm_name

string

--output_compression

string

Options

Name	Type & Properties	Description
--resolution	double required multiple	A parameter value controlling the coarseness of the clustering. Higher values lead to more clusters. Multiple values will result in clustering being performed multiple times.
--n_iterations	integer	Maximum number of iterations/levels of the Leiden algorithm. The algorithm will terminate after no more than this many iterations.
--random_state	integer	Random seed to initialise the optimization. Use this to increase reproducibility.

Name

Type & Properties

--resolution

double

required

multiple

--n_iterations

integer

--random_state

integer

rapids-singlecell options

Name	Type & Properties	Description
--theta	double	Scales modularity gain in the Leiden refinement phase, used to compute the probability of joining a random Leiden community.
--use_weights	boolean	If true, edge weights from the graph are used in the computation (placing more emphasis on stronger edges).

Name

Type & Properties

--theta

double

--use_weights

boolean

Scanpy options

Name	Type & Properties	Description
--flavor	string	Which package's implementation to use.

Name

Type & Properties

--flavor

string

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
modality: [ "rna" ]  
obsp_connectivities: [ "connectivities" ]  
device_type: [ "gpu" ]  
output: "$id.$key.output.h5mu"  
obsm_name: [ "leiden" ]  
resolution: [ 1 ]  
n_iterations: [ 100 ]  
random_state: [ 0 ]  
theta: [ 1 ]  
use_weights: [ true ]  
flavor: [ "leidenalg" ]  
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/tools/leiden/main.nf \  
  -params-file params.yaml

wrappers/tools/leiden

Inputs

Compute

Outputs

Options

rapids-singlecell options

Scanpy options

Run this component

Relationships

Used by

Uses