GTEX v9

Single-nucleus cross-tissue molecular reference maps to decipher disease gene function

cellxgene_census

Info

cellxgene_census/gtex_v9

2.99 GiB

02-02-2024

209126 × 28094

Description

Understanding the function of genes and their regulation in tissue homeostasis and disease requires knowing the cellular context in which genes are expressed in tissues across the body. Single cell genomics allows the generation of detailed cellular atlases in human tissues, but most efforts are focused on single tissue types. Here, we establish a framework for profiling multiple tissues across the human body at single-cell resolution using single nucleus RNA-Seq (snRNA-seq), and apply it to 8 diverse, archived, frozen tissue types (three donors per tissue). We apply four snRNA-seq methods to each of 25 samples from 16 donors, generating a cross-tissue atlas of 209,126 nuclei profiles, and benchmark them vs. scRNA-seq of comparable fresh tissues. We use a conditional variational autoencoder (cVAE) to integrate an atlas across tissues, donors, and laboratory methods. We highlight shared and tissue-specific features of tissue-resident immune cells, identifying tissue-restricted and non-restricted resident myeloid populations. These include a cross-tissue conserved dichotomy between LYVE1- and HLA class II-expressing macrophages, and the broad presence of LAM-like macrophages across healthy tissues that is also observed in disease. For rare, monogenic muscle diseases, we identify cell types that likely underlie the neuromuscular, metabolic, and immune components of these diseases, and biological processes involved in their pathology. For common complex diseases and traits analyzed by GWAS, we identify the cell types and gene modules that potentially underlie disease mechanisms. The experimental and analytical frameworks we describe will enable the generation of large-scale studies of how cellular and molecular processes vary across individuals and populations.

Preview

An AnnData object with n_obs × n_vars = 209126 × 28094 with slots:

obsm: X_pca
NameDescriptionTypeData typeSize
obs

soma_joinid

If the dataset was retrieved from CELLxGENE census, this is a unique identifier for the cell.vectorint64209126

dataset_id

Identifier for the dataset from which the cell data is derived, useful for tracking and referencing purposes.vectorcategory209126

assay

Type of assay used to generate the cell data, indicating the methodology or technique employed.vectorcategory209126

assay_ontology_term_id

Experimental Factor Ontology (`EFO:`) term identifier for the assay, providing a standardized reference to the assay type.vectorcategory209126

cell_type

Classification of the cell type based on its characteristics and function within the tissue or organism.vectorcategory209126

cell_type_ontology_term_id

Cell Ontology (`CL:`) term identifier for the cell type, offering a standardized reference to the specific cell classification.vectorcategory209126

development_stage

Stage of development of the organism or tissue from which the cell is derived, indicating its maturity or developmental phase.vectorcategory209126

development_stage_ontology_term_id

Ontology term identifier for the developmental stage, providing a standardized reference to the organism's developmental phase. If the organism is human (`organism_ontology_term_id == 'NCBITaxon:9606'`), then the Human Developmental Stages (`HsapDv:`) ontology is used. If the organism is mouse (`organism_ontology_term_id == 'NCBITaxon:10090'`), then the Mouse Developmental Stages (`MmusDv:`) ontology is used. Otherwise, the Uberon (`UBERON:`) ontology is used. vectorcategory209126

disease

Information on any disease or pathological condition associated with the cell or donor.vectorcategory209126

disease_ontology_term_id

Ontology term identifier for the disease, enabling standardized disease classification and referencing. Must be a term from the Mondo Disease Ontology (`MONDO:`) ontology term, or `PATO:0000461` from the Phenotype And Trait Ontology (`PATO:`). vectorcategory209126

donor_id

Identifier for the donor from whom the cell sample is obtained.vectorcategory209126

is_primary_data

Indicates whether the data is primary (directly obtained from experiments) or has been computationally derived from other primary data.vectorbool209126

self_reported_ethnicity

Ethnicity of the donor as self-reported, relevant for studies considering genetic diversity and population-specific traits.vectorcategory209126

self_reported_ethnicity_ontology_term_id

Ontology term identifier for the self-reported ethnicity, providing a standardized reference for ethnic classifications. If the organism is human (`organism_ontology_term_id == 'NCBITaxon:9606'`), then the Human Ancestry Ontology (`HANCESTRO:`) is used. vectorcategory209126

sex

Biological sex of the donor or source organism, crucial for studies involving sex-specific traits or conditions.vectorcategory209126

sex_ontology_term_id

Ontology term identifier for the biological sex, ensuring standardized classification of sex. Only `PATO:0000383`, `PATO:0000384` and `PATO:0001340` are allowed.vectorcategory209126

suspension_type

Type of suspension or medium in which the cells were stored or processed, important for understanding cell handling and conditions.vectorcategory209126

tissue

Specific tissue from which the cells were derived, key for context and specificity in cell studies.vectorcategory209126

tissue_ontology_term_id

Ontology term identifier for the tissue, providing a standardized reference for the tissue type. For organoid or tissue samples, the Uber-anatomy ontology (`UBERON:`) is used. The term ids must be a child term of `UBERON:0001062` (anatomical entity). For cell cultures, the Cell Ontology (`CL:`) is used. The term ids cannot be `CL:0000255`, `CL:0000257` or `CL:0000548`. vectorcategory209126

tissue_general

General category or classification of the tissue, useful for broader grouping and comparison of cell data.vectorcategory209126

tissue_general_ontology_term_id

Ontology term identifier for the general tissue category, aiding in standardizing and grouping tissue types. For organoid or tissue samples, the Uber-anatomy ontology (`UBERON:`) is used. The term ids must be a child term of `UBERON:0001062` (anatomical entity). For cell cultures, the Cell Ontology (`CL:`) is used. The term ids cannot be `CL:0000255`, `CL:0000257` or `CL:0000548`. vectorcategory209126

batch

A batch identifier. This label is very context-dependent and may be a combination of the tissue, assay, donor, etc.vectorcategory209126

size_factors

The size factors created by the normalisation method, if any.vectorfloat32209126
var

soma_joinid

If the dataset was retrieved from CELLxGENE census, this is a unique identifier for the feature.vectorint6428094

feature_id

Unique identifier for the feature, usually a ENSEMBL gene id.vectorobject28094

feature_name

A human-readable name for the feature, usually a gene symbol.vectorobject28094

hvg

Whether or not the feature is considered to be a 'highly variable gene'vectorbool28094

hvg_score

A ranking of the features by hvg.vectorfloat6428094
obsp

knn_connectivities

K nearest neighbors connectivities matrix.sparsematrixfloat32209126 × 209126

knn_distances

K nearest neighbors distance matrix.sparsematrixfloat64209126 × 209126
obsm

X_pca

The resulting PCA embedding.densematrixfloat32209126 × 50
varm

pca_loadings

The PCA loadings matrix.densematrixfloat3228094 × 50
layers

counts

Raw countssparsematrixfloat32209126 × 28094

normalized

Normalised expression valuessparsematrixfloat32209126 × 28094
uns

dataset_description

Long description of the dataset.atomicstr1

dataset_id

A unique identifier for the dataset. This is different from the `obs.dataset_id` field, which is the identifier for the dataset from which the cell data is derived.atomicstr1

dataset_name

A human-readable name for the dataset.atomicstr1

dataset_organism

The organism of the sample in the dataset.atomicstr1

dataset_reference

Bibtex reference of the paper in which the dataset was published.atomicstr1

dataset_summary

Short description of the dataset.atomicstr1

dataset_url

Link to the original source of the dataset.atomicstr1

knn

Supplementary K nearest neighbors data.dict3

normalization_id

Which normalization was usedatomicstr1

pca_variance

The PCA variance objects.dict2

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