Auto annotation with Nygen Insights

Auto annotations will create an AI report on cell type suggestions for each cluster of your chosen group. This feature uses the marker genes from each cluster to predict their cell types.

Key features

Under the hood, the auto annotation functionality integrates four external canonical marker databases:

• Human Commons Cell Atlas: A comprehensive resource for human cell type markers
• ACT: Animal Cell Type Atlas, providing markers across multiple species
• PanglaoDB: A database for single-cell RNA sequencing experiments from mouse and human
• CellMarker2: An updated version of the CellMarker database with expanded cell type information

These databases are consumed to generate initial cluster annotations based on the integrated databases. This, along with Cell Ontology database provides a really good context to LLMs for predicting granular cell types with high confidence.

Creating a new auto annotation report

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Steps

1. From the explorer page of your dataset, you can generate auto annotation reports using Nygen Insights.

2. Click on Generate New Insight and select auto annotation from the list of options.

3. Fill in the rest of the form for submission.

Required fields:

Select annotation species

The report will be generated based on marker genes, choose the species that matches best with your dataset.

Select group

Select from a list of the current groups or clusters to annotate.

💡Additional information

Providing more details on your dataset will give the LLM more context, this can improve the results and provide more relevant reports

4. The report will have a few minutes to generate. Once it’s done, you can access all your generated reports from the Nygen Insights panel. More on report content below.

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Report features

Auto annotations from Nygen Insight not only suggest cell type annotations, but also provide detailed supporting information, including marker genes that support or conflict with each cell type, confidence levels, and additional metrics. This automated assistance streamlines the manual curation process, allowing researchers to dedicate more time to focused investigations of rare cell types, subtle cellular states, and other detailed analyses.

Details

Each report will include the input parameters used which will help keep track of the context given to generate the report.

Each cluster of the selected group will be given a suggested cell type annotation. Below the cluster name, the coloured bar is given to indicate the confidence level of the predicted cell type.

Cell Ontology

This will open a new tab to the Ontology Lookup Service website page, where you can find the cell ontology details on the suggested cell type.

Use name

You can rename the cluster using the new cell annotation.

The report includes text details on what supported the cell annotations. This includes supporting marker genes in the cluster, as well as conflicting markers and anomalies which may lower the confidence of the auto annotation.

Alternative cell types to the current annotation and similar clusters are also suggested.

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