Module : Spikeless Pooled Normalization

Module : Spikeless Pooled Normalization

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

• Internal name : scpoolednormalization

• Avalaible : local mode

• Input Ports :

  • sce_object : SingleCellExperiment object (rds)

• Output Ports :

  • cellsoutput : normalized cells metadata (tsv)

• Optional parameters :

Parameter	Type	Description	Default Value
mode	string	Use All, Endogenous, or Nuclear genes	Nuclear
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, useful for large datasets)	FALSE
min_cluster_size	int	Minimum number of cells per cluster (at most half of the total number of cells)	100
force_positive	boolean	Whether to force for positive size factor values or not	FALSE
detection	int	Threshold to consider a gene expressed (used for gene filtering before normalizing)	1
n_cells	int	Expression threshold across cells 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 available for human and mouse cells)	FALSE
organism	string	Organism for cell cycle annotation (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>