Threshold/Discriminator

Overview of Threshold/Discriminator

Definition: A threshold, also known as a discriminator, is a set value that an electronic signal must exceed in order to be recorded as an event by the flow cytometer
Purpose in Flow Cytometry:
- Reduce Noise: To eliminate background noise and low-amplitude signals from being recorded as events
- Discriminate Events: To selectively record events of interest while ignoring unwanted events
- Improve Data Quality: By reducing noise and unwanted events, the overall quality of the data is improved
Key Concepts:
- Threshold Level: The specific value that the signal must exceed
- Trigger Parameter: The parameter that is used to determine whether the threshold is exceeded (e.g., forward scatter, side scatter, fluorescence channel)
- Event Recording: Only events that exceed the threshold level are recorded and analyzed
- Data Analysis: The threshold setting can affect the number of events recorded and the overall distribution of data

Single Threshold:
- Definition: A single value that the signal must exceed on a specific parameter
- Example: A threshold set on forward scatter to exclude debris and small particles
Multiple Thresholds:
- Definition: Multiple values that the signal must exceed on different parameters
- Example: A threshold set on forward scatter and a threshold set on side scatter to select a specific population of cells
Software Thresholds:
- Definition: Thresholds that are set and adjusted using software controls
- Advantages: More flexible and easier to adjust than hardware thresholds
Hardware Thresholds:
- Definition: Thresholds that are set using physical components on the flow cytometer
- Advantages: More stable and less susceptible to software glitches

Considerations:
- Cell Type: The size and complexity of the cells being analyzed
- Fluorophore Brightness: The intensity of the fluorescence signal
- Background Noise: The level of background noise in the system
- Experimental Goals: The specific objectives of the experiment
Methods:
1. Visual Inspection: Examine the data on a scatter plot or histogram to identify the region of interest
2. Control Samples: Use control samples (e.g., unstained cells) to determine the level of background noise
3. Titration: Titrate the threshold level to optimize the separation between positive and negative populations
4. Automated Thresholding: Use software algorithms to automatically set the threshold level based on the data

Definition: The parameter that is used to determine whether the threshold is exceeded
Common Trigger Parameters:
- Forward Scatter (FSC): Used to trigger on cells based on size
- Side Scatter (SSC): Used to trigger on cells based on granularity
- Fluorescence Channel: Used to trigger on cells based on fluorescence intensity
Considerations:
- Cell Population of Interest: Select a trigger parameter that is expressed by the cell population of interest
- Background Noise: Avoid trigger parameters with high levels of background noise
- Experiment Objectives: Select a trigger parameter that is relevant to the specific objectives of the experiment

Low Threshold:
- Advantages:
  - Captures more events
  - Detects rare cell populations
- Disadvantages:
  - Increases noise
  - Records unwanted events
  - Decreases data quality
High Threshold:
- Advantages:
  - Reduces noise
  - Records fewer unwanted events
  - Improves data quality
- Disadvantages:
  - Loses events
  - May miss rare cell populations

Objective: To find the optimal balance between capturing events of interest and reducing noise
Strategies:
1. Start with a Low Threshold: Begin with a low threshold to capture all possible events
2. Gradually Increase the Threshold: Gradually increase the threshold level while monitoring the data
3. Monitor the Noise Level: Pay close attention to the level of background noise
4. Optimize Separation: Adjust the threshold to optimize the separation between positive and negative populations
5. Confirm with Controls: Use control samples to confirm that the threshold setting is appropriate
General Considerations:
- If you are performing immunophenotyping, you will want to trigger on the cells of interest
  - If you are performing immunophenotyping on lymphocytes, trigger on CD45
- If you are performing rare event analysis, you want to cast a very wide net by setting the threshold low
- If you want to remove any carryover from the sheath fluid as well as remove debris, you will want to set the threshold on forward scatter (FSC)

Low Event Count:
- Possible Causes:
  - High threshold setting
  - Incorrect trigger parameter
  - Sample preparation issues
- Troubleshooting Steps:
  - Reduce threshold setting
  - Verify trigger parameter
  - Optimize sample preparation
High Background Noise:
- Possible Causes:
  - Low threshold setting
  - Contaminated samples
  - Incorrect instrument settings
- Troubleshooting Steps:
  - Increase threshold setting
  - Clean samples
  - Optimize instrument settings
Unexpected Event Populations:
- Possible Causes:
  - Incorrect threshold settings
  - Sample contamination
  - Instrument malfunction
- Troubleshooting Steps:
  - Verify threshold settings
  - Check for sample contamination
  - Inspect instrument for malfunctions

Threshold: A set value that an electronic signal must exceed in order to be recorded as an event
Discriminator: Another term for threshold
Trigger Parameter: The parameter that is used to determine whether the threshold is exceeded
Event Recording: The process of recording events that exceed the threshold level
Background Noise: Unwanted signals that interfere with the detection of true events