Pca
    Computes PCA coordinates, loadings and variance decomposition.
  
Info
ID: pca
Namespace: dimred
Links
Uses the implementation of scikit-learn [Pedregosa11]
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 2.1.1 -latest \
  -main-script target/nextflow/dimred/pca/main.nf \
  --helpRun command
Example of params.yaml
# Arguments
input: # please fill in - example: "input.h5mu"
modality: "rna"
# layer: "foo"
# var_input: "filter_with_hvg"
# output: "$id.$key.output.h5mu"
# output_compression: "gzip"
obsm_output: "X_pca"
varm_output: "pca_loadings"
uns_output: "pca_variance"
# num_components: 25
overwrite: false
# Nextflow input-output arguments
publish_dir: # please fill in - example: "output/"
# param_list: "my_params.yaml"nextflow run openpipelines-bio/openpipeline \
  -r 2.1.1 -latest \
  -profile docker \
  -main-script target/nextflow/dimred/pca/main.nf \
  -params-file params.yaml
Note
Replace -profile docker with -profile podman or -profile singularity depending on the desired backend.
Argument group
Arguments
| Name | Description | Attributes | 
|---|---|---|
--input | 
Input h5mu file | file, required, example: "input.h5mu" | 
--modality | 
string, default: "rna" | 
|
--layer | 
Use specified layer for expression values instead of the .X object from the modality. | string | 
--var_input | 
Column name in .var matrix that will be used to select which genes to run the PCA on. | string, example: "filter_with_hvg" | 
--output | 
Output h5mu file. | file, required, example: "output.h5mu" | 
--output_compression | 
The compression format to be used on the output h5mu object. | string, example: "gzip" | 
--obsm_output | 
In which .obsm slot to store the resulting embedding. | string, default: "X_pca" | 
--varm_output | 
In which .varm slot to store the resulting loadings matrix. | string, default: "pca_loadings" | 
--uns_output | 
In which .uns slot to store the resulting variance objects. | string, default: "pca_variance" | 
--num_components | 
Number of principal components to compute. Defaults to 50, or 1 - minimum dimension size of selected representation. | integer, example: 25 | 
--overwrite | 
Allow overwriting .obsm, .varm and .uns slots. | boolean_true |