Bbknn leiden

Run bbknn followed by leiden clustering and run umap on the result.

Info

ID: bbknn_leiden
Namespace: multiomics/integration

Links

Source

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 0.10.0 -latest \
  -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \
  --help

Run command

Example of params.yaml

# Inputs
id: # please fill in - example: "foo"
input: # please fill in - example: "dataset.h5mu"
layer: "log_normalized"
modality: "rna"

# Outputs
# output: "$id.$key.output.h5mu"

# Bbknn
obsm_input: "X_pca"
obs_batch: "sample_id"
uns_output: "bbknn_integration_neighbors"
obsp_distances: "bbknn_integration_distances"
obsp_connectivities: "bbknn_integration_connectivities"
n_neighbors_within_batch: 3
n_pcs: 50
# n_trim: 123

# Clustering options
obs_cluster: "bbknn_integration_leiden"
leiden_resolution: 1

# UMAP options
obsm_umap: "X_leiden_bbknn_umap"

# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"

nextflow run openpipelines-bio/openpipeline \
  -r 0.10.0 -latest \
  -profile docker \
  -main-script ./workflows/multiomics/integration/bbknn_leiden/main.nf \
  -params-file params.yaml

Note

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

Argument groups

Inputs

Name	Description	Attributes
`--id`	ID of the sample.	`string`, required, example: `"foo"`
`--input`	Path to the sample.	`file`, required, example: `"dataset.h5mu"`
`--layer`	use specified layer for expression values instead of the .X object from the modality.	`string`, default: `"log_normalized"`
`--modality`	Which modality to process.	`string`, default: `"rna"`

Outputs

Name	Description	Attributes
`--output`	Destination path to the output.	`file`, required, example: `"output.h5mu"`

Bbknn

Name	Description	Attributes
`--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: `"sample_id"`
`--uns_output`	Mandatory .uns slot to store various neighbor output objects.	`string`, default: `"bbknn_integration_neighbors"`
`--obsp_distances`	In which .obsp slot to store the distance matrix between the resulting neighbors.	`string`, default: `"bbknn_integration_distances"`
`--obsp_connectivities`	In which .obsp slot to store the connectivities matrix between the resulting neighbors.	`string`, default: `"bbknn_integration_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`

Clustering options

Name	Description	Attributes
`--obs_cluster`	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 resolutions specified in ‘–leiden_resolution’.	`string`, default: `"bbknn_integration_leiden"`
`--leiden_resolution`	Control the coarseness of the clustering. Higher values lead to more clusters.	`double`, default: `1`

UMAP options

Name	Description	Attributes
`--obsm_umap`	In which .obsm slot to store the resulting UMAP embedding.	`string`, default: `"X_leiden_bbknn_umap"`

Authors

Mauro Saporita (author)
Povilas Gibas (author)

Visualisation

flowchart LR
    p0(Input)
    p2(toSortedList)
    p4(flatMap)
    p10(bbknn)
    p12(join)
    p20(leiden)
    p22(join)
    p30(umap)
    p32(join)
    p40(move_obsm_to_obs)
    p42(join)
    p48(Output)
    p0-->p2
    p2-->p4
    p4-->p12
    p4-->p10
    p10-->p12
    p12-->p22
    p12-->p20
    p20-->p22
    p22-->p32
    p22-->p30
    p30-->p32
    p32-->p42
    p32-->p40
    p40-->p42
    p42-->p48