Knn

Performs label transfer from reference to query using KNN classifier

Info

ID: knn
Namespace: labels_transfer

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 1.0.1 -latest \
  -main-script target/nextflow/labels_transfer/knn/main.nf \
  --help

Run command

Example of params.yaml

# Learning parameters
n_neighbors: # please fill in - example: 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/labels_transfer/knn/main.nf \
  -params-file params.yaml

Note

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

Argument groups

Input dataset (query) arguments

Name	Description	Attributes
--input	The query data to transfer the labels to. Should be a .h5mu file.	file, required
--modality	Which modality to use.	string, default: "rna"
--input_obsm_features	The .obsm key of the embedding to use for the classifier’s inference. If not provided, the .X slot will be used instead. Make sure that embedding was obtained in the same way as the reference embedding (e.g. by the same model or preprocessing).	string, example: "X_integrated_scanvi"

Reference dataset arguments

Name	Description	Attributes
--reference	The reference data to train classifiers on.	file, example: "https:/zenodo.org/record/6337966/files/HLCA_emb_and_metadata.h5ad"
--reference_obsm_features	The .obsm key of the embedding to use for the classifier’s training. Make sure that embedding was obtained in the same way as the query embedding (e.g. by the same model or preprocessing).	string, required, default: "X_integrated_scanvi"
--reference_obs_targets	The .obs key of the target labels to tranfer.	List of string, default: "ann_level_1", "ann_level_2", "ann_level_3", "ann_level_4", "ann_level_5", "ann_finest_level", multiple_sep: ";"

Outputs

Name	Description	Attributes
--output	The query data in .h5mu format with predicted labels transfered from the reference.	file, required
--output_obs_predictions	In which .obs slots to store the predicted information. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_pred" suffix.	List of string, multiple_sep: ";"
--output_obs_uncertainty	In which .obs slots to store the uncertainty of the predictions. If provided, must have the same length as --reference_obs_targets. If empty, will default to the reference_obs_targets combined with the "_uncertainty" suffix.	List of string, multiple_sep: ";"
--output_uns_parameters	The .uns key to store additional information about the parameters used for the label transfer.	string, default: "labels_transfer"

Learning parameters

Name	Description	Attributes
--n_neighbors	Number of nearest neighbors to use for classification	integer, required

Authors

• Vladimir Shitov (author)