workflows/integration/scanorama_leiden

Description

Run scanorama integration followed by neighbour calculations, leiden clustering and run umap on the result.

Type

nextflow_script

License

MIT

Links

Repository

Contributors

Launch

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
id: "run"  
layer: [ "log_normalized" ]  
modality: [ "rna" ]  
output: "$id.$key.output.h5mu"  
uns_neighbors: [ "scanorama_integration_neighbors" ]  
obsp_neighbor_distances: [ "scanorama_integration_distances" ]  
obsp_neighbor_connectivities: [ "scanorama_integration_connectivities" ]  
obs_batch: [ "sample_id" ]  
obsm_input: [ "X_pca" ]  
obsm_output: [ "X_scanorama" ]  
knn: [ 20 ]  
batch_size: [ 5000 ]  
sigma: [ 15 ]  
approx: [ true ]  
alpha: [ 0.1 ]  
obs_cluster: [ "scanorama_integration_leiden" ]  
leiden_resolution: [ 1 ]  
obsm_umap: [ "X_leiden_scanorama_umap" ]  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/openpipeline.git \  
  -revision v4.2.0 \  
  -main-script target/nextflow/workflows/integration/scanorama_leiden/main.nf \  
  -params-file params.yaml

Inputs

Name	Type & Properties	Description
--id	string required	ID of the sample.
--input	file required	Path to the sample.
--layer	string	use specified layer for expression values instead of the .X object from the modality.
--modality	string	Which modality to process.

Name

Type & Properties

--id

string

required

--input

file

required

--layer

string

--modality

string

Outputs

Name	Type & Properties	Description
--output	file required output	Destination path to the output.

Name

Type & Properties

--output

file

required

output

Neighbour calculation

Name	Type & Properties	Description
--uns_neighbors	string	In which .uns slot to store various neighbor output objects.
--obsp_neighbor_distances	string	In which .obsp slot to store the distance matrix between the resulting neighbors.
--obsp_neighbor_connectivities	string	In which .obsp slot to store the connectivities matrix between the resulting neighbors.

Name

Type & Properties

--uns_neighbors

string

--obsp_neighbor_distances

string

--obsp_neighbor_connectivities

string

Scanorama integration options

Name	Type & Properties	Description
--obs_batch	string	Column name discriminating between your batches.
--obsm_input	string	.obsm slot that points to embedding to run scanorama on.
--obsm_output	string	The name of the field in adata.obsm where the integrated embeddings will be stored after running this function. Defaults to X_scanorama.
--knn	integer	Number of nearest neighbors to use for matching.
--batch_size	integer	The batch size used in the alignment vector computation. Useful when integrating very large (>100k samples) datasets. Set to large value that runs within available memory.
--sigma	double	Correction smoothing parameter on Gaussian kernel.
--approx	boolean	Use approximate nearest neighbors with Python annoy; greatly speeds up matching runtime.
--alpha	double	Alignment score minimum cutoff

Name

Type & Properties

--obs_batch

string

--obsm_input

string

--obsm_output

string

--knn

integer

--batch_size

integer

--sigma

double

--approx

boolean

--alpha

double

Clustering options

Name	Type & Properties	Description
--obs_cluster	string	Prefix for the .obs keys under which to add the cluster labels. Newly created columns in .obs will be created from the specified value for '--obs_cluster' suffixed with an underscore and one of the resolutions specified in '--leiden_resolution'.
--leiden_resolution	double multiple	Control the coarseness of the clustering. Higher values lead to more clusters.

Name

Type & Properties

--obs_cluster

string

--leiden_resolution

double

multiple

Umap options

Name	Type & Properties	Description
--obsm_umap	string	In which .obsm slot to store the resulting UMAP embedding.

Name

Type & Properties

--obsm_umap

string