Downsampling

Step

Description

Gate Downsampling

This pipeline steps allow to downsample events using a gate of interest as selection method. This is useful when the subsequent steps of the pipeline should be only run on the events within a specific gate of interest.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s). One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.

The Gate option allows to select the gate to use for this downsampling step.

Interval Downsampling

Performs Interval Sampling on the input population.

Please refer to the Sampling Options chapter of the manual for more details on interval sampling.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s). One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.

The Sampling Size field allows to define how many events to sample.

Mask Downsampling

Mask downsampling allows users to remove events with a value of zero. This is useful if any of the upstream pipeline step generates a Downsampling mask and events with a value of zero in that mask have to be removed at some point of the pipeline. This step performs downsampling on the input population, using the parameters selected in the Parameter Options list (e.g. a Downsampling Mask parameter by upstream steps).

Parameters can be filtered or sorted to assist in the selection of parameters when multiple parameters are available in the template file. Using the Filter: field a user can remove unwanted parameters from view to simplify selection.  For example, if a user only wanted to select area parameters typing "-A" in the field would reduce the number of parameters seen in the parameter list. By right clicking in the parameters section, you can use Sort Ascending, Sort Descending, or Unsorted to easily manage parameter ordering and facilitate parameter selection.  In the right click menu, you can easily select parameters by utilizing Check All, Uncheck All, Check Selected, Uncheck Selected, Invert Selection on All. The options Check Selected and Uncheck Selected allow for using the shift key or Ctrl key to multi-select parameters and check or uncheck them all simultaneously.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s). One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.

The Mask Merging Style section of the dialog allows the user to choose between the following options:

•Cell must be non-zero in ALL selected parameter. Any values that are a zero for the selected parameters will be excluded and only non-zero values will be kept. If a cell has at least one zero value among the selected parameters, then that cell is removed.

•Cell must be non-zero in ANY of the selected parameter. If a cell has a value of zero in all the selected parameters, than that cell is removed. If a cell has at least one value which is not zero, than the cell is kept.

Random Downsampling

Performs Random Downsampling on the input population.

An internal seed is set so that when reopening the layout, the same sampled events are selected.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s). One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.

The Sampling Size field allows to define how many events to sample.

Generate New Random Seed. The Random Seed is a number which is used by the random number generator to generate the N random values. The random number generator will use the Random Seed value and perform a series of math operations on it which result in N random values. A seed can be set to make results reproducible over the time when the Random Sampling is run on the same data. The seed can be changed by either clicking on the Generate New Random Seed button or by manually inserting a seed in the field. In FCS Express, the default Random Seed is 6.

Target Density Downsampling

Performs Density-Dependent Downsampling on the input population, using the parameters selected in the Parameter Options list. Parameters can be filtered or sorted to assist in the selection of parameters when multiple parameters are available in the template file. Using the Filter: field a user can remove unwanted parameters from view to simplify selection.  For example, if a user only wanted to select area parameters typing "-A" in the field would reduce the number of parameters seen in the parameter list. By right clicking in the parameters section, you can use Sort Ascending, Sort Descending, or Unsorted to easily manage parameter ordering and facilitate parameter selection.  In the right click menu, you can easily select parameters by utilizing Check All, Uncheck All, Check Selected, Uncheck Selected, Invert Selection on All.  The options Check Selected and Uncheck Selected allow for using the shift key or Ctrl key to multi-select parameters and check or uncheck them all simultaneously.

Please refer to the Target Density Downsampling chapter of the manual for more details on the following options:

Specify Density percentiles, Sample Size, Alpha, Min Density, Target Density, Local Density Method, and Add Local Density as Output.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s) One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.

Weighted Density Downsampling

Performs Weighted Density Downsampling on the input population, using the parameters selected in the Parameter Options list. Parameters can be filtered or sorted to assist in the selection of parameters when multiple parameters are available in the template file. Using the Filter: field a user can remove unwanted parameters from view to simplify selection.  For example, if a user only wanted to select area parameters typing "-A" in the field would reduce the number of parameters seen in the parameter list. By right clicking in the parameters section, you can use Sort Ascending, Sort Descending, or Unsorted to easily manage parameter ordering and facilitate parameter selection.  In the right click menu, you can easily select parameters by utilizing Check All, Uncheck All, Check Selected, Uncheck Selected, Invert Selection on All.  The options Check Selected and Uncheck Selected allow for using the shift key or Ctrl key to multi-select parameters and check or uncheck them all simultaneously.

Please refer to the Weighted Sampling Options chapter of the manual for more details on the following options:

Specify Sample Size, Alpha, Weight, Local Density Method, and Add Local Density as Output.

The How should the data be downsampled option allows two choices:

oDownsampling Existing Parameters. No mask parameter is created and only the downsampled events will be available downstream this pipeline step.

oCreate new mask parameter(s). One (or two; see below) new parameter is created. The name and the nature of this parameter can be customized with the How should the new parameter be created option (see below).

The How should the new parameters be created option allows to:

oDefine the Downsampling mask names prefix. This is defaulted to Downsampling mask but can be edited. Editing this prefix is especially useful to distinguish mask parameters generated by different downsampling pipeline steps.

oDefine whether the new parameter should contain data saved as Classification Values. When this option is used, sampled events will be assigned with a "Include" value in that parameter while unsampled events will be assigned with a "Exclude" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

oDefine whether the new parameter should contain data saved as Numeric (Float) Values. When this option is used, sampled events will be assigned with a "1" value in that parameter while unsampled events will be assigned with a "0" value in that parameter. The editable field at the right of this option allows to customize the suffix to use for this parameter.

Note: when both the Save as Classification Values and the Save as Numeric (Float) value options are used, two mask parameters will be created.