Module : Spikeless Pooled Normalization

Module : Spikeless Pooled Normalization

This module estimates size factors for each cell (check the scran paper for a detailed account).

• Internal name : scpoolednormalization

• Avalaible : local mode

• Input Ports :

  • matrix : filtered expression matrix (tsv)
  • cells : filtered cells metadata (tsv)
  • genes : features metadata (tsv)

• Output Ports :

  • cellsoutput : normalized cells metadata (tsv)

• Optional parameters :

Parameter	Type	Description	Default Value
mode	string	Use All, Endogenous, or Nuclear genes	Endogenous
color_by	string	Name of the column from the design file to use for cell plotting	Condition
precluster	boolean	Whether to precluster cells or not (can decrease computation time)	False
min_cluster_size	int	Minimum number of cell per cluster (at most half of the number of cells)	100
force_positive	boolean	Whether to force for positive size factor values or not	False
detection	int	Detection threshold to consider a gene expressed, used for gene filtering before normalizing	1
n_cells	int	Number of detection to keep a gene, used for gene filtering before normalizing	1
length_correction	boolean	Whether to correct for feature length or not before plotting (increases computation time)	False
cell_cycle	boolean	Whether to annotate cells for cell cycle or not (only for human and mouse cells)	False
organism	string	Organism for cell cycle annotation, should be one of : mus_musculus or homo_ sapiens	mus_musculus

• Configuration example

<step id="normalization" skip="false">
        <module>scpoolednormalization</module>
        <parameters>
           <parameter>
              <name>mode</name>
              <value>Endogenous</value>
           </parameter>
           <parameter>
              <name>precluster</name>
              <value>False</value>
           </parameter>
           <parameter>
              <name>cell_cycle</name>
              <value>False</value>
           </parameter>
        </parameters>
</step>