# Quick Start

### Overview

This quick start guide introduces a sample workflow for preliminary clustering of cell populations using CODEX MAV. As development progresses, this page will be updated with better analysis workflows.

### Clustering

Open an experiment.

Select 'Analysis > X-Shift Clustering'. Use default parameters and select all relevant markers.

![](/files/-LiEjwksXO-nyi5szmQF)

Colors represent the mean marker intensity for all cells within the population. Red represents higher intensity. Color scheme may be changed to 'rainbow' in the preferences menu. Hover your cursor over the cell to see the exact value.

If there are enough clusters with high SNR expressions, select all clusters and add as populations. If not, re-run clustering with a lower k-value.

![Add Populations](/files/-LedMZlpf5aHsdz26_cs)

Select 'Color by Dendogram'.

![Color by Dendogram](/files/-LiEkKWAoRlmUZTA7UkM)

This function auto-colors all populations by their clustering hierarchy.

![](/files/-LiEmqrwVk6EZUpbmPjP)

Name populations for their marker expression by clicking populations in the 'Name' column. If any populations should be combined, select the target populations and click on 'Combine Selected Populations'.

![Combine Selected Populations](/files/-LedOBK_87xBRZOHc3c5)

Larger populations may be split further by re-clustering. Select the target population and re-run clustering using 'Analysis > X-Shift Clustering'. When re-clustering populations, delete the original population prior to adding the new clusters to the population window as to avoid overlap.

![Delete Population](/files/-LedNnLV2grX9KB0FKVW)

Larger populations may impede visualization of smaller, more interesting populations.

![](/files/-LiEmue4UKJNV3YtbF7K)

Hide certain populations by toggling their checkbox in the 'Visibility' column.

![](/files/-LiEnRogi-xe34E2OdMj)

Validate your clusters by comparing select cells to the original marker image. Turn off all other populations and focus on one cluster at a time.

![Toggle Visibility for All Populations](/files/-LedNOC0tTwx9Qjm6PMq)

Once populations of significance are annotated, save your analysis state using 'File > Save analysis as...'.


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