> For the complete documentation index, see [llms.txt](https://documentation.panomics.bio/documentation/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://documentation.panomics.bio/documentation/analyses/analysis-workbench/sample-cell-explorer/normalization.md).

# Normalization

The first step in any new analysis is to perform normalization. The normalization command performs different actions, depending on the workflow. A [`Standard Compute`](/documentation/compute-runtimes/codeless-compute.md) runtime is required.

To run normalization, click the `Normalize` button in the top bar of workbench.

### Single cell RNA-seq:

{% stepper %}
{% step %}

### Normalize total

Normalizes each cell by total counts over all genes, so that every cell has the same total count after normalization (target = 10,000).
{% endstep %}

{% step %}

### Log transform

Takes log1p of normalized counts.
{% endstep %}

{% step %}

### Compute highly variable genes

Uses the `seurat` flavor of the algorithm with a gene threshold of 2,000.
{% endstep %}

{% step %}

### Scale counts

Uses a max value of 10.
{% endstep %}
{% endstepper %}

### Bulk RNA-seq

{% stepper %}
{% step %}

### Normalize counts

Uses TMM (Trimmed Mean of M component) to make samples comparable.
{% endstep %}

{% step %}

### Log transform

Takes log1p of normalized counts.
{% endstep %}

{% step %}

### Scale counts

Uses a max value of 10.
{% endstep %}
{% endstepper %}

{% hint style="info" %}
For each dataset, Panomics keeps a copy of the raw counts and a copy of the unscaled normalized and log-transformed counts alongside the scaled version.
{% endhint %}


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