Module : threshold filtering

Module : threshold-filtering

This module removes bad quality cells from the dataset based on user-set thresholds.

• Internal name : threshold-filtering

• Avalaible : local mode

• Input Ports :

  • matrix : initial count matrix (tsv)
  • cells : initial cells metadata (tsv)
  • genes : genes metadata (tsv)

• Output Ports :

  • completcellsoutput : initial cells metadata (tsv) (completed with quality metrics)
  • matrixoutput : filtered count matrix (tsv)
  • cellsoutput : filtered cells metadata (tsv)

• Optional parameters :

Parameter	Type	Description	Default Value
detection_threshold	integer	Minimal number of reads to consider a feature as detected	10
expression_option	string	Type of feature to consider (Endogenous, Nuclear or All)	Endogenous
expression_threshold	integer	Minimal number of detected features	4000
reads_threshold	integer	Minimal number of mapped reads to keep a cell	200 000
prop_mt	float	Maximum proportion of reads mapping to mitochondrial features	0.1
prop_sp	float	Maximum proportion of reads mapping to exogenous features	0.5
nb_filters	int	Minimum number of failures triggering removal	1

• Configuration example

<step id="QC" skip="false">
	<module>threshold-filtering</module>
	<parameters>
		<parameter>
			<name>expression_option</name>
			<value>Endogenous</value>	
		</parameter>
		<parameter>
			<name>reads_threshold</name>
			<value>500000</value>	
		</parameter>
		<parameter>
			<name>expression_threshold</name>
			<value>1500</value>	
		</parameter>
	  </parameters>
</step>

Interpreting output files

Scatter Plot

After cleaning data, the module produces two scatter plot, showing all cells in term of number of features (y-axis) and number of reads (x-axis).

The first one shows all cells, and the filtering thresholds. Cells in red are eliminated.

The second one shows the remaining cells after filtering. At the end of the filtering, cells should behave like a mixture of Gaussians, i.e. you can wrap them in a given number of ellipses.