1. Catalog
  2. Data
  3. Single-Cell (SOMA)
  • Home
  • What is TileDB?
  • Get Started
  • Explore Content
  • Accounts
    • Individual Accounts
      • Apply for the Free Tier
      • Profile
        • Overview
        • Cloud Credentials
        • Storage Paths
        • REST API Tokens
        • Credits
    • Organization Admins
      • Create an Organization
      • Profile
        • Overview
        • Members
        • Cloud Credentials
        • Storage Paths
        • Billing
      • API Tokens
    • Organization Members
      • Organization Invitations
      • Profile
        • Overview
        • Members
        • Cloud Credentials
        • Storage Paths
        • Billing
      • API Tokens
  • Catalog
    • Introduction
    • Data
      • Arrays
      • Tables
      • Single-Cell (SOMA)
      • Genomics (VCF)
      • Biomedical Imaging
      • Vector Search
      • Files
    • Code
      • Notebooks
      • Dashboards
      • User-Defined Functions
      • Task Graphs
      • ML Models
    • Groups
    • Marketplace
    • Search
  • Collaborate
    • Introduction
    • Organizations
    • Access Control
      • Introduction
      • Share Assets
      • Asset Permissions
      • Public Assets
    • Logging
    • Marketplace
  • Analyze
    • Introduction
    • Slice Data
    • Multi-Region Redirection
    • Notebooks
      • Launch a Notebook
      • Usage
      • Widgets
      • Notebook Image Dependencies
    • Dashboards
      • Dashboards
      • Streamlit
    • Preview
    • User-Defined Functions
    • Task Graphs
    • Serverless SQL
    • Monitor
      • Task Log
      • Task Graph Log
  • Scale
    • Introduction
    • Task Graphs
    • API Usage
  • Structure
    • Why Structure Is Important
    • Arrays
      • Introduction
      • Quickstart
      • Foundation
        • Array Data Model
        • Key Concepts
          • Storage
            • Arrays
            • Dimensions
            • Attributes
            • Cells
            • Domain
            • Tiles
            • Data Layout
            • Compression
            • Encryption
            • Tile Filters
            • Array Schema
            • Schema Evolution
            • Fragments
            • Fragment Metadata
            • Commits
            • Indexing
            • Array Metadata
            • Datetimes
            • Groups
            • Object Stores
          • Compute
            • Writes
            • Deletions
            • Consolidation
            • Vacuuming
            • Time Traveling
            • Reads
            • Query Conditions
            • Aggregates
            • User-Defined Functions
            • Distributed Compute
            • Concurrency
            • Parallelism
        • Storage Format Spec
      • Tutorials
        • Basics
          • Basic Dense Array
          • Basic Sparse Array
          • Array Metadata
          • Compression
          • Encryption
          • Data Layout
          • Tile Filters
          • Datetimes
          • Multiple Attributes
          • Variable-Length Attributes
          • String Dimensions
          • Nullable Attributes
          • Multi-Range Reads
          • Query Conditions
          • Aggregates
          • Deletions
          • Catching Errors
          • Configuration
          • Basic S3 Example
          • Basic TileDB Cloud
          • fromDataFrame
          • Palmer Penguins
        • Advanced
          • Schema Evolution
          • Advanced Writes
            • Write at a Timestamp
            • Get Fragment Info
            • Consolidation
              • Fragments
              • Fragment List
              • Consolidation Plan
              • Commits
              • Fragment Metadata
              • Array Metadata
            • Vacuuming
              • Fragments
              • Commits
              • Fragment Metadata
              • Array Metadata
          • Advanced Reads
            • Get Fragment Info
            • Time Traveling
              • Introduction
              • Fragments
              • Array Metadata
              • Schema Evolution
          • Array Upgrade
          • Backends
            • Amazon S3
            • Azure Blob Storage
            • Google Cloud Storage
            • MinIO
            • Lustre
          • Virtual Filesystem
          • User-Defined Functions
          • Distributed Compute
          • Result Estimation
          • Incomplete Queries
        • Management
          • Array Schema
          • Groups
          • Object Management
        • Performance
          • Summary of Factors
          • Dense vs. Sparse
          • Dimensions vs. Attributes
          • Compression
          • Tiling and Data Layout
          • Tuning Writes
          • Tuning Reads
      • API Reference
    • Tables
      • Introduction
      • Quickstart
      • Foundation
        • Data Model
        • Key Concepts
          • Indexes
          • Columnar Storage
          • Compression
          • Data Manipulation
          • Optimize Tables
          • ACID
          • Serverless SQL
          • SQL Connectors
          • Dataframes
          • CSV Ingestion
      • Tutorials
        • Basics
          • Ingestion with SQL
          • CSV Ingestion
          • Basic S3 Example
          • Running Locally
        • Advanced
          • Scalable Ingestion
          • Scalable Queries
      • API Reference
    • AI & ML
      • Vector Search
        • Introduction
        • Quickstart
        • Foundation
          • Data Model
          • Key Concepts
            • Vector Search
            • Vector Databases
            • Algorithms
            • Distance Metrics
            • Updates
            • Deployment Methods
            • Architecture
            • Distributed Compute
          • Storage Format Spec
        • Tutorials
          • Basics
            • Ingestion & Querying
            • Updates
            • Deletions
            • Basic S3 Example
            • Running Locally
          • Advanced
            • Versioning
            • Time Traveling
            • Consolidation
            • Distributed Compute
            • RAG LLM
            • LLM Memory
            • File Search
            • Image Search
            • Protein Search
          • Performance
        • API Reference
      • ML Models
        • Introduction
        • Quickstart
        • Foundation
          • Basics
          • Storage
          • Cloud Execution
          • Why TileDB for Machine Learning
        • Tutorials
          • Ingestion
            • Data Ingestion
              • Dense Datasets
              • Sparse Datasets
            • ML Model Ingestion
          • Management
            • Array Schema
            • Machine Learning: Groups
            • Time Traveling
    • Life Sciences
      • Single-cell
        • Introduction
        • Quickstart
        • Foundation
          • Data Model
          • Key Concepts
            • Data Structures
            • Use of Apache Arrow
            • Join IDs
            • State Management
            • TileDB Cloud URIs
          • SOMA API Specification
        • Tutorials
          • Data Ingestion
          • Bulk Ingestion Tutorial
          • Data Access
          • Distributed Compute
          • Basic S3 Example
          • Multi-Experiment Queries
          • Appending Data to a SOMA Experiment
          • Add New Measurements
          • SQL Queries
          • Running Locally
          • Shapes in TileDB-SOMA
          • Drug Discovery App
        • Spatial
          • Introduction
          • Foundation
            • Spatial Data Model
            • Data Structures
          • Tutorials
            • Spatial Data Ingestion
            • Access Spatial Data
            • Manage Coordinate Spaces
        • API Reference
      • Population Genomics
        • Introduction
        • Quickstart
        • Foundation
          • Data Model
          • Key Concepts
            • The N+1 Problem
            • Architecture
            • Arrays
            • Ingestion
            • Reads
            • Variant Statistics
            • Annotations
            • User-Defined Functions
            • Tables and SQL
            • Distributed Compute
          • Storage Format Spec
        • Tutorials
          • Basics
            • Basic Ingestion
            • Basic Queries
            • Export to VCF
            • Add New Samples
            • Deleting Samples
            • Basic S3 Example
            • Basic TileDB Cloud
          • Advanced
            • Scalable Ingestion
            • Scalable Queries
            • Query Transforms
            • Handling Large Queries
            • Annotations
              • Finding Annotations
              • Embedded Annotations
              • External Annotations
              • Annotation VCFs
              • Ingesting Annotations
            • Variant Statistics
            • Tables and SQL
            • User-Defined Functions
            • Sample Metadata
            • Split VCF
          • Performance
        • API Reference
          • Command Line Interface
          • Python API
          • Cloud API
      • Biomedical Imaging
        • Introduction
        • Foundation
          • Data Model
          • Key Concepts
            • Arrays
            • Ingestion
            • Reads
            • User Defined Functions
          • Storage Format Spec
        • Quickstart
        • Tutorials
          • Basics
            • Ingestion
            • Read
              • OpenSlide
              • TileDB-Py
          • Advanced
            • Batched Ingestion
            • Chunked Ingestion
            • Machine Learning
              • PyTorch
            • Napari
    • Files
  • API Reference
  • Self-Hosting
    • Installation
    • Upgrades
    • Administrative Tasks
    • Image Customization
      • Customize User-Defined Function Images
      • AWS ECR Container Registry
      • Customize Jupyter Notebook Images
    • Single Sign-On
      • Configure Single Sign-On
      • OpenID Connect
      • Okta SCIM
      • Microsoft Entra
  • Glossary

On this page

  • Add SOMA
  • Overview
  • Contents
  • Metadata
  • Sharing & activity
  • Settings
  • Rename SOMA
  • Delete SOMA
  1. Catalog
  2. Data
  3. Single-Cell (SOMA)

Single-Cell (SOMA)

single cell (soma)
catalog
TileDB is an ideal solution for managing, structuring, and analyzing single-cell data
TileDB structures single-cell data with arrays and groups

TileDB is an ideal solution for managing single-cell data. It introduces a novel data model called SOMA, which allows it to structure single-cell data for unprecedented performance and interoperability with popular tools. Read the Structure: Single-cell section for more details on SOMA, TileDB’s programmatic features, and tool integrations. This section focuses mostly on TileDB’s catalog features on the UI console.

Add SOMA

You can programmatically ingest various different single-cell file formats into the TileDB SOMA model for single-cell, which is covered in detail in section Structure: Single-cell. Similar to arrays, you can create a single-cell dataset first, and register it in a second step, either from the UI or programmatically.

From the UI, you can register an existing single-cell dataset as follows:

  1. Navigate to the Assets tab from the right menu.
  2. Select the Add asset button.
  3. From the pop-up window, select Data, expand the Life Sciences choice, select SOMA, and then Register SOMA group.
  4. From the new window, select your Cloud credentials that can access the physical location where the SOMA dataset is stored (you must have already set these up in your account Settings), input the physical location of your SOMA dataset in the Register from… field, add a SOMA name for this dataset, and optionally select a License and add Tags that facilitate catalog search.
  5. Select Register.

Registering a SOMA dataset to the TileDB catalog. Registering a SOMA dataset to the TileDB catalog.

You can programmatically register a SOMA dataset as follows:

  • Python
tiledb.cloud.asset.register(
    storage_uri="s3://<bucket>/<soma_name>",
    namespace="<account>",  # Optional, you may register it under your username, or one of your organizations
    name="<soma_name>",  # Could be different from the physical SOMA dataset name
    description=None,  # Optional, this will appear under Overview
    credentials_name="<credentials>",  # Required, which AWS credentials from your account can access the SOMA dataset.
    # You must have already added your AWS credentials in your account settings
)

A registered SOMA dataset will appear under Assets -> Data -> SOMA in the TileDB catalog.

Registered SOMA datasets in the TileDB catalog. Registered SOMA datasets in the TileDB catalog.

Overview

In this screen, you can find basic information about the SOMA dataset:

  • SOMA name - This appears at the very top of the screen, and consists of the account name and the name you provided to the SOMA dataset when registering it.

  • Description - If you provided a description to the SOMA dataset (programmatically or in Settings), it is visible here. The description is indexed and searchable in the catalog. Therefore, it’s recommended to add a meaningful description for all your assets.

  • License - The type of license for the SOMA dataset, especially if you are making this publicly available.

  • Tags - These can be used for efficient search in the catalog.

  • UUID - The unique identifier for the SOMA dataset.

  • Original URI - The location on cloud storage where the SOMA dataset is physically stored.

  • TileDB URI - The unique resource identifier for TileDB, based on which you can call the SOMA dataset when coding. It comprises the namespace identifier and the UUID of the SOMA dataset.

  • Author - Which account registered the SOMA dataset.

  • Permissions - What rights the current user has on this SOMA dataset. Possible values are READ and ADMIN.

  • Number of assets - TileDB models the SOMA dataset as a TileDB group, which may contain other TileDB groups and TileDB arrays.

Referring to the SOMA dataset programmatically

It is important to understand how to refer to your SOMA dataset programmatically. You can do it in two ways:

  1. Using the TileDB URI format tiledb://<account>/<soma_name>. This is the most user-friendly way, but TileDB allows duplicated SOMA dataset names, and if you have a SOMA dataset with a non-unique name, this will throw an error.
  2. Using the TileDB URI from the asset’s Overview tab (that is, the URI with format tiledb://<account>/<UUID>). TileDB URIs referencing the asset’s UUID are unique. Thus, this method will always work.

Getting basic information in the SOMA dataset overview. Getting basic information in the SOMA dataset overview.

You can programmatically get overview information about the SOMA dataset with the following command:

  • Python
# The following will return a JSON file with various info about the SOMA dataset.
tiledb.cloud.asset.info("tiledb://<account>/<soma_name>")

Contents

TileDB models SOMA datasets as TileDB groups, which may contain TileDB arrays and other TileDB groups. The contents of a SOMA dataset are visible in the Contents tab, where you can browse them and see their details.

The SOMA dataset contents that may include arrays and other groups. The SOMA dataset contents that may include arrays and other groups.

Metadata

SOMA datasets may be associated with metadata in the form of key-value pairs, which is visible in the Metadata tab.

The metadata screen of the SOMA dataset. The metadata screen of the SOMA dataset.

Sharing & activity

The Sharing screen allows you to securely share your SOMA dataset with other TileDB users, whereas the Activity screen shows you the various accesses performed on the SOMA dataset by you or any other user with whom you have shared your SOMA dataset. They are both covered in detail in the Collaborate section.

Settings

In the SOMA dataset settings, you can modify the following:

  • Description - Note that this is indexed and, thus, searchable in the TileDB catalog.
  • Tags - These can be used for efficient search in the catalog.
  • License - The type of license for the SOMA dataset, especially if you are making this publicly available.
  • Make public - If you wish to share the SOMA dataset with all the TileDB users. This will appear in the Marketplace tab in the left navigation menu. If you make a SOMA dataset public, you can easily change it back to private in the same manner.
  • Change cloud credentials - Credentials should be provided so that TileDB can securely access the SOMA dataset on the cloud store where it is physically stored.
  • Rename SOMA - Read the Rename SOMA subsection below.
  • Delete SOMA - Read the Delete SOMA subsection below.

The settings screen of the SOMA dataset. The settings screen of the SOMA dataset.

You can programmatically update some SOMA dataset settings with the following command:

  • Python
tiledb.cloud.asset.update_info(
    uri="tiledb://<account>/<soma_name>",
    description=None,  # Optional - A new description
    name=None,  # Optional - A new name for the SOMA dataset
    tags=None,  # Optional - SOMA dataset tags that will be searchable in the catalog
    access_credentials_name=None,  # Optional - The cloud credentials that access the SOMA dataset (should already exist in your account settings)
)

To make a SOMA dataset public programmatically, run the following:

  • Python
tiledb.cloud.asset.share(
    "tiledb://<account>/<soma_name>", namespace="public", permissions="read"
)

Rename SOMA

A useful property of the TileDB catalog and the way it registers SOMA datasets is that you can easily rename a SOMA dataset, without physically moving it, thus avoiding the very expensive copying operations entailed in object stores when physically renaming/moving file objects. You can rename a SOMA dataset from the Settings tab.

You can programmatically rename a SOMA dataset as follows:

  • Python
tiledb.cloud.asset.update_info(
    "`tiledb://<account>/<previous_name>`", name="<new_name>"
)
Warning

Take caution when renaming SOMA datasets, as any URIs including the previous SOMA dataset name will no longer work.

Delete SOMA

When deleting a SOMA dataset, you have two options:

  • Unregister: This operation removes the SOMA dataset from the TileDB catalog, but it does not physically remove it from the object store. Since the SOMA dataset will persist on storage, you can register it again in the TileDB catalog in the future.
  • Delete: This operation both unregisters and physically removes the SOMA dataset from storage. Note that this operation cannot be undone.

You can delete the SOMA dataset from the Settings tab, which will prompt you to choose among the two operations above.

The two options when removing a SOMA dataset. The two options when removing a SOMA dataset.

You can also programmatically delete or unregister the SOMA dataset as follows:

  • Python
# Unregister a SOMA dataset
tiledb.cloud.asset.deregister(uri="tiledb://<account>/<soma_name>")

# Delete a SOMA dataset
tiledb.cloud.asset.delete(uri="tiledb://<account>/<soma_name>")
Tables
Genomics (VCF)