filter/filter_with_scrublet

Description

Doublet detection using the Scrublet method (Wolock, Lopez and Klein, 2019).
The method tests for potential doublets by using the expression profiles of
cells to generate synthetic potential doubles which are tested against cells.
The method returns a "doublet score" on which it calls for potential doublets.

For the source code please visit https://github.com/AllonKleinLab/scrublet.

For 10x we expect the doublet rates to be:
Multiplet Rate (%) - # of Cells Loaded - # of Cells Recovered
~0.4% ~800 ~500
~0.8% ~1,600 ~1,000
~1.6% ~3,200 ~2,000
~2.3% ~4,800 ~3,000
~3.1% ~6,400 ~4,000
~3.9% ~8,000 ~5,000
~4.6% ~9,600 ~6,000
~5.4% ~11,200 ~7,000
~6.1% ~12,800 ~8,000
~6.9% ~14,400 ~9,000
~7.6% ~16,000 ~10,000

Type

python_script

License

MIT

Links

Repository

Contributors

Launch

Run this component

Run the following command to execute this component with Nextflow:

cat > params.yaml <<'EOM'  
modality: [ "rna" ]  
output: "$id.$key.output.h5mu"  
obs_name_filter: [ "filter_with_scrublet" ]  
obs_name_doublet_score: [ "scrublet_doublet_score" ]  
min_counts: [ 2 ]  
min_cells: [ 3 ]  
min_gene_variablity_percent: [ 85 ]  
num_pca_components: [ 30 ]  
distance_metric: [ "euclidean" ]  
id: "run"  
publish_dir: "output/"  
EOM

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

Arguments

Name	Type & Properties	Description
--input	file required	Input h5mu file
--modality	string	Which modality from the input MuData file to process.
--layer	string	Input layer to use as data for calculating doublets. .X is used not specified.
--output	file output	Output h5mu file.
--obs_name_filter	string	In which .obs slot to store a boolean array corresponding to which observations should be filtered out.
--do_subset	boolean_true	Whether to subset before storing the output.
--obs_name_doublet_score	string	Name of the doublet scores column in the obs slot of the returned object.
--expected_doublet_rate	double	The estimated fraction of doublets as from the experimental setup.
--stdev_doublet_rate	double	Uncertainty in the expected doublet rate.
--n_neighbors	integer	Number of neighbors used to construct the KNN classifier of observed transcriptomes and simulated doublets.
--sim_doublet_ratio	double	Number of doublets to simulate relative to the number of observed transcriptomes.
--min_counts	integer	The number of minimal UMI counts per cell that have to be present for initial cell detection.
--min_cells	integer	The number of cells in which UMIs for a gene were detected.
--min_gene_variablity_percent	double	Used for gene filtering prior to PCA. Keep the most highly variable genes (in the top min_gene_variability_pctl percentile), as measured by the v-statistic [Klein et al., Cell 2015].
--num_pca_components	integer	Number of principal components to use during PCA dimensionality reduction.
--distance_metric	string	The distance metric used for computing similarities.
--scrublet_score_threshold	double	Manual doublet score threshold. Cells with a doublet score above this value are classified as doublets. If not provided, the threshold is determined automatically by Scrublet.
--allow_automatic_threshold_detection_fail	boolean_true	When scrublet fails to automatically determine the double score threshold, allow the component to continue and set the output columns to NA.
--output_compression	string	Compression format to use for the output AnnData and/or Mudata H5 files. By default no compression is applied.

Name

Type & Properties

--input

file

required

--modality

string

--layer

string

--output

file

output

--obs_name_filter

string

--do_subset

boolean_true

--obs_name_doublet_score

string

--expected_doublet_rate

double

--stdev_doublet_rate

double

--n_neighbors

integer

--sim_doublet_ratio

double

--min_counts

integer

--min_cells

integer

--min_gene_variablity_percent

double

--num_pca_components

integer

--distance_metric

string

--scrublet_score_threshold

double

--allow_automatic_threshold_detection_fail

boolean_true

--output_compression

string