Steps

1 Load and open fully stained unmixed sample 00:21
2 Apply time and singlet gating 00:53
3 Gate live cells and cells of interest 01:56
4 Verify marker expression and population resolution 02:42
5 Select population and parameters for dimensionality reduction 03:48
6 Run t-SNE algorithm with basic parameters 05:08
7 Validate marker co-localization in t-SNE plot 05:27

Molecular Biology Current Protocols

Assessment of Data Quality Using Expert Gating and Dimensionality Reduction Algorithms

Name: Assessment of Data Quality Using Expert Gating and Dimensionality Reduction Algorithms
Uploaded: 2026-06-17
Duration: 6 min 23 s
Description: For more information, see the associated protocol: Panel Optimization for High-Dimensional Immunophenotyping Assays Using Full-Spectrum Flow Cytometry https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/cpz1.222

Protocol

Difficulty

intermediate

Steps

Load and open fully stained unmixed sample

Open the fully stained unmixed FCS file in flow cytometry analysis software (such as FlowJo). This file contains the data that needs to be quality assessed.

▶ 00:21

Apply time and singlet gating

Create a time gate to ensure events were recorded during stable flow. Then apply forward scatter height versus area gating and side scatter height versus area gating to isolate single cells on the 45-degree diagonal.

▶ 00:53

Gate live cells and cells of interest

Gate on live cells using viability stain and high forward scatter to exclude debris. Then select the population of interest (lymphocytes for this T cell panel) based on the experimental design.

▶ 01:56

Verify marker expression and population resolution

Examine all marker combinations to confirm expected co-localization patterns (such as CD3+ T cells without CD19+ B cell overlap) and assess spreading between related markers. Verify that readout markers are clearly resolved from negative populations.

▶ 02:42

Select population and parameters for dimensionality reduction

Access the t-SNE algorithm from the workspace menu and select the clean gated population (CD3+ T cells). Choose only the markers that were not used for gating, excluding viability dye, CD19, and CD3 parameters.

▶ 03:48

Run t-SNE algorithm with basic parameters

Execute the t-SNE dimensionality reduction algorithm using default parameters on the selected population and markers.

▶ 05:08

Validate marker co-localization in t-SNE plot

Plot the t-SNE parameters on x versus y axes and color by different markers to verify that markers co-localize exactly where expected. Iterate through multiple marker combinations (such as CD4 and CD8) to confirm proper unmixing and data quality.

▶ 05:27

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