integrate/scarches

Description

Performs reference mapping with scArches

Type

python_script

Contributors

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
modality: [ "rna" ]  
dataset_name: [ "test_dataset" ]  
output: "$id.$key.output"  
model_output: "$id.$key.model_output"  
obsm_output: [ "X_integrated_scanvi" ]  
early_stopping_monitor: [ "elbo_validation" ]  
early_stopping_patience: [ 45 ]  
early_stopping_min_delta: [ 0 ]  
reduce_lr_on_plateau: [ true ]  
lr_factor: [ 0.6 ]  
lr_patience: [ 30 ]  
id: "run"  
publish_dir: "output/"  
EOM

nextflow run https://packages.viash-hub.com/vsh/openpipeline.git \  
  -revision 1.0.0 \  
  -main-script target/nextflow/integrate/scarches/main.nf \  
  -params-file params.yaml

Inputs

Name	Type & Properties	Description
--input -i	file required	Input h5mu file to use as a query
--modality	string
--reference -r	file required	Path to the directory with reference model or a web link. For HLCA use https://zenodo.org/record/6337966/files/HLCA_reference_model.zip
--dataset_name	string	Name of query dataset to use as a batch name. If not set, name of the input file is used

Name

Type & Properties

--input

-i

file

required

--modality

string

--reference

-r

file

required

--dataset_name

string

Outputs

Name	Type & Properties	Description
--output -o	file required output	Output h5mu file.
--output_compression	string	The compression format to be used on the output h5mu object.
--model_output	file output	Output directory for model
--obsm_output	string	In which .obsm slot to store the resulting integrated embedding.

Name

Type & Properties

--output

-o

file

required

output

--output_compression

string

--model_output

file

output

--obsm_output

string

Early stopping arguments

Name	Type & Properties	Description
--early_stopping	boolean	Whether to perform early stopping with respect to the validation set.
--early_stopping_monitor	string	Metric logged during validation set epoch.
--early_stopping_patience	integer	Number of validation epochs with no improvement after which training will be stopped.
--early_stopping_min_delta	double	Minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute change of less than min_delta, will count as no improvement.

Name

Type & Properties

--early_stopping

boolean

--early_stopping_monitor

string

--early_stopping_patience

integer

--early_stopping_min_delta

double

Learning parameters

Name	Type & Properties	Description
--max_epochs	integer required	Number of passes through the dataset, defaults to (20000 / number of cells) * 400 or 400; whichever is smallest.
--reduce_lr_on_plateau	boolean	Whether to monitor validation loss and reduce learning rate when validation set `lr_scheduler_metric` plateaus.
--lr_factor	double	Factor to reduce learning rate.
--lr_patience	double	Number of epochs with no improvement after which learning rate will be reduced.

Name

Type & Properties

--max_epochs

integer

required

--reduce_lr_on_plateau

boolean

--lr_factor

double

--lr_patience

double