Cell Types Support: tutorials, protocols, and more
This support page is a catalog of Allen Institute's resources to help better understand cell types. The first section is "What is..." lists introductory information on cell type topics. The second section is "How to..." lists more technical resources such as tutorials, protocols, use cases, and more. The third section is "Putting it all together" is a key to link research focus to related scientific tool to primary paper to taxonomy used.
Each resource has additional information such as that resource's citation, any related papers, and/or related scientific tools. Click on the to view to the listed resource.
Page Contents
What is...: What is a cell type? | What is transcriptomics? | What is a taxonomy? | What is a UMAP? | What is Patch-Seq?
How to..: How to understand cell type nomenclature | How to replicate our Patch-Seq | How to replicate our RNA-Seq | How to use Cell Type Knowledge Explorer | How to use ABC Atlas | How to use MapMyCells
Putting it altogether: Mouse (Healthy: Whole Brain, Visual & Motor Cortex, Hippocampus) | Human (Healthy: Whole Brain, Motor Cortex, MTG) | Human (Alzheimer's: MTG & DLPFC) | Marmoset (Motor Cortex)
What is...?
Introductory resources
Here are Allen Institute resources to help you understand the fundamentals of cell types and the research methods used to study cell types; including Patch-Seq, taxonomies, UMAPs, and more. These sections are designed for those who are unfamilar with cell type topics to help introduce them to the concepts.
What is a cell type?
Cells within a type exhibit similar structure and function that are distinct from cells in other types.
Learn from our Executive Vice President & Director of Brain Science, Hongkui Zeng, on the overview of cell types from the roots in evolution & development to the approaches in how to characterize, while also providing a roadmap for the future.
|
Type of resource |
Review Paper |
|
Citation |
Zeng H. What is a cell type and how to define it? Cell. 2022 Jul 21;185(15):2739-2755 |
Cell Types 101 Webinar focuses on an introduction to the study of cell types! It covers evolving cell type definitions, cell types across species, the types of data used to define cell types, and the importance of having standard definitions for cell types.
|
Type of resource |
Webinar |
|
Citation |
What is transcriptomics?
The study of RNA expression (the transcriptome) and how it differs between cells/tissues/conditions.
This webinar is tutorial on Allen Cell Types Database. Starting at 4:13, we give an overview of single cell or nuclues transcriptomics.
Note: Webinar is from 2021; the taxonomies presented in the webinar are not the latest taxonomies from the Institute, as newer taxonomies have been created since 2021.
|
Type of resource |
Webinar |
|
Citation |
What is a (cell type) taxonomy?
A cell type taxonomy is a specific analysis organizing cells into groups (or types), applied to a specific set of data, and saved in a standard format. Cell types are annotated with data-driven and historical information about their characteristics.
User-friendly tutorial that goes step by step on how cell type taxonomies are created, with linking to data from Allen Cell Types Database in the end. This is a great web-interface that is perfect for students to experts to begin exploring what a taxonomy is.
|
Type of resource |
Interactive walkthrough |
|
Releated Tool |
|
|
Related Paper |
Tasic, B., et al. (2016) Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. |
|
Citation |
'What is a taxonomy?' webinar is focused on the systematic classification of cell types and their hierarchical relationships. Much like species taxonomy (family, genus, species, etc.), researchers at the Allen Institute and their collaborators are working to create a standard taxonomy for cell types.
|
Type of resource |
Webinar |
|
Citation |
What is a UMAP?
Uniform Manifold Approximation and Projection (UMAP). UMAPs are helpful ways of displaying many types of data and are often referred to as one type of dimensionality reduction tool.
UMAP is a common way to visualize cell types taxonomies. Learn how to interpret and analyze these graphs.
|
Type of resource |
Guide |
|
Citation |
Meuler, M. (2023). What is a UMAP?. https://alleninstitute.org/resource/what-is-a-umap/ |
What is Patch-Seq?
Patch-Seq is modified version of Patch-Clamp, with the additional steps of extracting the nucleus to obtain transcriptomics and preserving the cell body to obtain morphology.
Patch-Seq was developed around late 2010s, with Allen Institute helping to optimize the technique. Here is a 2016 Allen Institute team talk giving an overview of Patch-Seq.
|
Type of resource |
Team Talk |
|
Citation |
This webinar from 2024 gives an focus on overview of what Patch-Seq is, and how that data is used in the tool, Cell Type Knowledge Explorer.
|
Type of resource |
Webinar |
|
Related Tool |
|
|
Citation |
How to...
Technical Protocols, Guides, Useful Supplemental Information
These are Allen Institute resources to explain how to use our datasets, replicate our experiments with protocols, and links to tables with important metadata and features definitions. These sections are designed for scientists who are interested in more techincal support in their cell types reserach.
How to understand cell type nomenclature
Understand the framework for developing nomenclatures—called the Common Cell Type Nomenclature, or CCN.
|
Type of resource |
Guide |
|
Related Paper |
Miller, J. A., et al. (2020) Common cell type nomenclature for the mammalian brain eLife 9:e59928 |
How to replicate our Patch-Seq protocols and analysis
Adopting the Patch-seq technique in a lab can be daunting. To make adoption as simple as possible, this GitHub provides a starting point for labs interested in using the Patch-seq technique or refining their existing technique. Specifically, this resource consists of three components: (1) a step-by-step optimized Patch-seq protocol (2) the Multichannel Igor Electrophysiology Suite (MIES) software package and (3) an R library that uses a modified workflow.
|
Type of resource |
GitHub Protocol Hub |
|
Related Paper |
|
|
Citation |
Overview of the various steps and tools to generate data across species and brain regions in Patch-Seq.
|
Type of resource |
Community Forum |
|
Citation |
Check the various protocols |
From our electrophysiology team, this is detailed protocol to obtain electrophysiological recordings and cellular contents from neurons in postnatal mouse and/or human brain slices.
|
Type of resource |
Protocol |
|
Used in Related Tools |
|
|
Used in Datasets |
|
|
Related Paper |
Lee, B. R., et al. (2021) Scaled, high fidelity electrophysiological, morphological, and transcriptomic cell characterization |
|
Citation |
IPFX is a Python package for computing intrinsic cell features from electrophysiology data. That can perform cell data quality control (e.g. resting potential stability), detect action potentials and their features (e.g. threshold time and voltage), calculate features of spike trains (e.g., adaptation index), and calculate stimulus-specific cell features
|
Type of resource |
GitHub Repository |
|
Used in Datasets |
|
|
Citation |
Here is your one-stop shop for the Allen Institute’s free, open-source neuron reconstruction software, protocols, and analysis scripts for generating and analyzing image-based, quantitative, 3D morphologies for your own research.
|
Type of resource |
Protocol, Software, Analysis |
|
Used in Related Tools |
|
|
Used in Datasets |
|
|
Citation |
Protocol to generate full-length cDNA from single cells, or nuclei, using Takara SMARTer V4.
|
Type of resource |
Protocol |
|
Used in Related Tools |
|
|
Used in Datasets |
|
|
Citation |
The electrophysiology and morphology feature definitions are used for all our Patch-Seq datasets. This is from “NIHMS1691616-supplement-Supplementary_Figures” in Gouwens, Sorensen, Berg, et al. 2019, starts at page 73 for electrophysiology and page 75 for morphology.
|
Type of resource |
Supplemental Table |
|
Related Tools |
Allen Cell Types Database |
|
Related Datasets |
|
|
Citation |
How to replicate our RNA-Seq laboratory protocols
This page includes protocols for SMART-Seq and Nextera XT, FACs, and tissue preparation and analysis & clustering links.
|
Type of resource |
Protocols, Analysis |
|
Citation |
See protocols.io "Metadata" for individual citations |
To monitor for a consistent, high-quality sampling of single-cell and single-nucleus RNA-Seq data, we have controls used in each application sample. These controls for mouse and human data are available to download for you to use in your own experiments.
|
Type of resource |
Supportive Data |
|
Citation |
See protocols.io "Metadata" for individual citations |
How to use Cell Type Knowledge Explorer
Scientific tool for entry point for exploration of individual cell type taxonomies for human, marmoset and mouse primary motor cortex
Learn from the scientists behind our Cell Types Knowledge Explorer about why it is made, key findings, and a walkthrough of the tool itself.
|
Type of resource |
Tutorial |
|
Related Tool |
|
|
Related Papers |
Patch-Seq (Mouse): Scala, F., et al. (2021). Phenotypic variation of transcriptomic cell types in mouse motor cortex. Nature. DOI: 0.1038/s41586-020-2907-3 |
|
Citation |
These use cases were designed to show researchers how to use the mouse data in the Cell Type Knowledge Explorer for their own research questions. The case titled “Experimental Design” shows how the Cell Type Knowledge Explorer can be used to guide research questions.
|
Type of resource |
Guide |
|
Related Tool |
Python code for you to your own generate data visualizations that was used in the Cell Type Knowledge Explorer.
|
Type of resource |
GitHub |
|
Related Tool |
|
|
Citation |
How to use ABC Atlas
The Allen Brain Cell (ABC) Atlas provides a platform for visualizing multimodal single cell data across the mammalian brain and aims to empower researchers to explore and analyze multiple whole-brain datasets simultaneously.
From our product managers of ABC Atlas, here is a user guide to help you navigate all the features of ABC Atlas.
|
Type of resource |
User Guide |
|
Related Tool |
|
|
Related Papers |
Mouse (Spatial & Non-Spatial Transcriptomics, Coronal): Yao et al. (2023) A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain. DOI 10.1038/s41586-023-06812-z. |
These use cases were designed to show researchers how to use the Whole Human Brain data in the ABC Atlas for their own research questions. The two use cases titled “Experimental Design” show how the ABC Atlas can be used to guide research questions, while the use case titled “Scientific Knowledge” shows how the ABC Atlas can be used studying and/or writing a literature review. The “coding” in the third use case shows users how to access the raw data for the Whole Human Brain using Jupyter notebooks.
|
Type of resource |
Use Case |
|
Related Tool |
Learn from the scientists behind the new collection of studies from the BRAIN Initiative Cell Atlas Network (biccn.org) and published in Nature on Dec 14, 2023
|
Type of resource |
Webinar |
|
Related Tool |
|
|
Related Paper |
Brain Initiative Cell Census Network 2.0, Nature 2023 Paper Package |
|
Citation |
Excel files of the acronyms found in ABC Atlas with their corresponding full name, type of acronym (“types”), and the identifiers (“primary identifier”, “secondary identifier”, and “tertiary identifier”). See the table below for list of the types and identifiers used in the Excel file.
|
Type of resource |
Supplemental |
|
"Types" |
anatomical structure |
|
"identifiers" |
Suggested identifier look-up links UBERON (Uber-anatomy ontology): https://www.ebi.ac.uk/ols4/ontologies/uberon OR https://rgd.mcw.edu/rgdweb/homepage/ CL (Cell ontology): https://www.ebi.ac.uk/ols4/ontologies/cl MBA* (Mouse Brain Atlas): https://bioregistry.io/registry/mba *Go to our Mouse Brain Atlas by searching either acronym or full name to find the anatomical structure. You cannot search the identifier number in the Mouse Brain Atlas directly. ENSEMBL: https://www.ensembl.org/ NCBIGene: https://www.ncbi.nlm.nih.gov/gene ABAGene: https://mouse.brain-map.org/ |
|
Related Tool |
List of the 500 Gene panel used in the whole brain mouse. This is from the supplemental table 6 in Yao, et al. 2023
|
Type of resource |
Supplemental |
|
Related Tool |
Detailed information for each cluster, neurotransmitter information, overall marker genes, main dissection region, and more. This is from the supplemental table 7 in Yao, et al. 2023.
|
Type of resource |
Supplemental |
|
Related Tool |
Updated Supplemental Table 7 from Yao et al., 2023 for comparing clusters in whole mouse brain taxonomy vs. clusters from Yao, et al. 2021 whole cortex taxonomy.
|
Type of resource |
Supplemental (unpublished) |
|
Related Tool |
Detailed information for each subcluster, neurotransmitter information, overall marker genes, main dissection region, and more. This is from the supplemental table for Siletti, et al. 2023 (unpublished)
|
Type of resource |
Supplemental (unpublished) |
|
Related Tool |
See all the updates & patches to ABC Atlas.
|
Type of resource |
Update Notes |
|
Related Tool |
ABC Atlas Dataset Descriptions
| Data | Paper | ABC Atlas Dataset Name | # of genes | # of samples/donors | Plane of Sections |
|---|---|---|---|---|---|
|
10x scRNAseq |
Yao et al., 2023 |
“10x ScRNAseq whole brain” |
31,113 |
317 mice |
n/a |
|
MERFISH Zeng |
Yao et al., 2023 |
"MERFISH-C57BL6J-638850"
|
500 |
1 mouse |
Coronal |
|
MERFISH Zhuang |
Zhang et al., 2023 |
"Zhuang-ABCA-1/2/3/4" |
1,122 |
4 mice |
Coronal & Sagittal |
|
10x snRNAseq - Neuronal |
Siletti et al., 2023 |
"Human Brain Cell Type Diversity - Neurons" |
51,820 |
3 whole brains, 1 M1 section |
n/a |
|
10x snRNAseq - Non-neuronal |
Siletti et al., 2023 |
"Human Brain Cell Type Diversity - Non-neuronal Cells" |
51,820 |
3 whole brains, 1 M1 section |
n/a |
|
10x snRNAseq |
Gabitto & Travaglini et al., 2024 |
“SEA-AD snRNAseq – MTG and DLPFC” |
36,266 |
84 |
n/a |
|
MERFISH |
Gabitto & Travaglini et al., 2024 |
“SEA-AD MERFISH – MTG” |
140 |
24 |
Coronal |
MapMyCells allows you discover what cell types your transcriptomics and spatial data corresponds with by comparing you data to our massive, high-quality reference datasets.
Learn from one of our scientists behind MapMyCells on how to use it, what type of data it accepts, what taxonomies are built of fit, which algorithms to select, and peek under the hood on how it works.
|
Type of resource |
Webinar |
|
Related Tool |
|
|
Citation |
MapMyCells needs cell by gene matrix where rows are “cells” and columns are “genes”, which need to be in file format h5ad. This guide provides more details about your input file limits, how to create h5ad from csv, example h5ad files and more!
|
Type of resource |
Guide |
|
Related Tool |
Unsure what algorithm or taxonomy to select in MapMyCells? This guide is for you.
|
Type of resource |
Guide |
|
Related Tool |
The online version of MapMyCells will provide accurate cell type assignments for user-inputted data in most cases. However, there are some situations when using the direct scripts may be more appropriate: (1) if the reference taxonomy you are interested in is not one currently included in MapMyCells, (2) if the data set you have is quite large, (3) if you'd like to include these algorithms as part of an analysis pipeline, or (4) if you need to select a different set of genes for mapping (e.g., for mapping MERFISH data).
|
Type of resource |
Workbook Guide |
|
Related Tool |
BICCN and BICAN
Most of these resources are part of the Brain Initiative Cell Census Network (BICCN) and/or Brain Initiative Cell Atlas Network (BICAN). The Allen Institute serves as the coordinating member of this network.
|
Type of resource |
Review Paper |
|
Citation |
Hawrylycz, M., et al. (2023). A guide to the BRAIN Initiative Cell Census Network data ecosystem |
Putting it all together
The associated tool::paper::taxonomy::research focus
This table links the research topic (species, brain area of interest, and technique) to the related tool, the related dataset, the related paper, and the related taxonomy.
Research model, area of interestTECHNIQUE |
Related Tool |
Project Summary |
Related Paper |
Related Taxonomy |
|---|---|---|---|---|
|
Mouse, Whole Brain Spatial transcriptomics & single cell RNA-Seq |
||||
|
Mouse, Whole Brain Spatial transcriptomics |
A molecularly defined and spatially resolved cell atlas of the whole mouse brain |
|||
|
Mouse, Whole Cortex & Hippocampus Single cell RNA-Seq (SMART-Seq and 10x) |
Cell types taxonomy (2021) |
|||
|
Mouse, Primary Visual Cortex & Anterior Lateral Motor Cortex Single cell RNA-Seq |
Transcriptomic cell types in the mouse brain: SMART-seq cells |
|||
|
Mouse, Primary Motor Cortex |
Taxonomy embedded in the download files for the "10x Chromium v3 (Broad)" dataset |
|||
|
Mouse, Primary Motor Cortex |
Taxonomy embedded in the download files for the first seven datasets |
|||
|
Mouse, Primary Visual Cortex |
||||
|
Mouse, (majority) Visual Cortex |
N/A |
No associated transcriptomic taxonomy |
||
|
Human, Whole Brain |
||||
|
Human, Multiple Cortical Areas |
*some of the data |
Taxonomy for transcriptomic explorer |
||
|
Human, Primary Motor Cortex |
||||
|
Human, Middle Temporal Gyrus Single nucleus RNA-Seq |
Hodge, R. D., Bakken, T. E., et al. (2019). Conserved cell types with divergent features in human versus mouse cortex. DOI: 0.1038/s41586-019-1506-7. |
|||
|
Human, Middle Temporal Gyrus, Alzhiemer's Disease |
Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) - Spatial transcriptomics - MERFISH |
|||
|
Human, Middle Temporal Gyrus, Alzhiemer's Disease |
|
Seattle Alzheimer's Disease Brain Cell Atlas (SEA-AD) - 10x single nucleus RNAseq |
||
|
Marmoset, Primary Motor Cortex |
A Molecular and Cellular Atlas of the Marmoset Brain - Single nucleus sequencing |
This page was last updated May 2024.
This page creation was supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under Award Number U24NS133077. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Your browser is out-of-date!
Update your browser to view this website correctly.