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

Launch

Arguments

Name	Type & Properties	Description
--input	file required	Input h5mu file
--modality	string
--layer	string	Input layer to use as data for calculating doublets. .X is used not specified.
--output	file output	Output h5mu file.
--output_compression	string	The compression format to be used on the output h5mu object.
--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.

Name

Type & Properties

--input

file

required

--modality

string

--layer

string

--output

file

output

--output_compression

string

--obs_name_filter

string

--do_subset

boolean_true

--obs_name_doublet_score

string

--expected_doublet_rate

double

--stdev_doublet_rate

double