Module : MAD filtering

Module : MAD-filtering

This module removes bad quality cells from the dataset based on median absolute deviation (MAD).

• Internal name : MAD-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 detect (Endogenous, Nuclear or All)	Endogenous
n_Mad	integer	Maximal number of median absolute deviations for number of reads and number of detected features	5
direction	string	Direction to consider for MAD filtering : lower, upper or both	both
groups	string	Name of the column for cell grouping, if cells are in one group value is Null	Null
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>MAD-filtering</module>
	<parameters>
		<parameter>
			<name>n_Mad</name>
			<value>3</value>	
		</parameter>
		<parameter>
			<name>direction</name>
			<value>lower</value>	
		</parameter>
		<parameter>
			<name>groups</name>
			<value>CellType</value>	
		</parameter>
	  </parameters>
</step>

Interpreting output files

Scatter Plot

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

The first one shows all cells. The red ones are those being 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.