single-cell
C2S-Pythia-410m-diverse-single-and-multi-cell-tasksvandijklab_-_C2S-Pythia-410m-diverse-single-and-multi-cell-tasks-ggufC2S-Pythia-410m-diverse-single-and-multi-cell-tasks-GGUFcellfinder_single_channel_defaultSingle_Cell_ClassifierC2S-Pythia-410m-diverse-single-and-multi-cell-tasks-GGUFC2S-Pythia-410m-diverse-single-and-multi-cell-tasks-mlx-4Bitvandijklab_-_C2S-Pythia-410m-diverse-single-and-multi-cell-tasks-awq
single-cell-brain-zarr
Single-Cell Brain Zarr Collection
Production-ready brain single-cell RNA-seq data exported from the CellxGene Census into native Zarr stores for chunked, on-demand access on the Hugging Face Hub.
Why Zarr
Single-cell expression matrices get impractical fast if you treat them like ordinary dense files. Zarr is the point of this repo: it makes large atlas-scale data usable without forcing users to download or materialize the whole matrix before they can do anything useful.… See the full description on the dataset page: https://huggingface.co/datasets/KokosDev/single-cell-brain-zarr.gene-expression-single-cell-mouse
A single-cell transcriptomic atlas characterizes ageing tissues in the mouse
Code to download and process this dataset is available in: https://github.com/seanome/2025-longevity-x-ai-hackathon
Dataset structure is originally from AnnData.
Descriptions of each data file is below.
Data Files
This dataset contains multiple parquet files, one for each sheet in the original Excel file:
gene-expression-single-cell-mouse_*.parquet - Data files containing gene expression and… See the full description on the dataset page: https://huggingface.co/datasets/longevity-db/gene-expression-single-cell-mouse.SingleCell-Unseen-Benchmark
SingleCell-Unseen-Benchmark
Overview
SingleCell-Unseen-Benchmark is a large-scale unseen single-cell transcriptomic benchmark designed to systematically evaluate foundation models on cell identification and cell type tracing tasks.The benchmark covers tumor, stem, neural, and normal cell populations, with a particular emphasis on unseen data distributions, including rare cell types, cross-dataset generalization, and heterogeneous tumor states.
In addition to curated… See the full description on the dataset page: https://huggingface.co/datasets/SiatBioInf/SingleCell-Unseen-Benchmark.aging-gene-expression-single-cell-mouse
A single-cell transcriptomic atlas characterizes ageing tissues in the mouse
https://www.nature.com/articles/s41586-020-2496-1#Sec2
Code to download and process this dataset is available in: https://github.com/seanome/2025-longevity-x-ai-hackathon
Dataset structure is originally from AnnData.
Descriptions of each data file is below.
Data Files
This dataset contains multiple parquet files, one for each sheet in the original Excel file:… See the full description on the dataset page: https://huggingface.co/datasets/longevity-db/aging-gene-expression-single-cell-mouse.DeepSpot2Cell-HEST1k-Virtual-SingleCell
DeepSpot2Cell Virtual Single-Cell Spatial Transcriptomics
Virtual single-cell gene expression predictions for Visium spatial transcriptomics
samples, generated by DeepSpot2Cell.
Overview
This dataset provides predicted single-cell gene expression profiles for
Visium samples across 5,000 genes. The predictions were generated by running
a trained DeepSpot2Cell model on preprocessed Visium data from HEST-1k.
DeepSpot2Cell uses a permutation-invariant DeepSet… See the full description on the dataset page: https://huggingface.co/datasets/GravityBeng/DeepSpot2Cell-HEST1k-Virtual-SingleCell.gtex-single-cell-rnaseq
GTEx Single-Cell RNA-seq Dataset
This repository provides tools to create a Hugging Face dataset from GTEx single-nucleus RNA-seq data, transforming the hierarchical H5AD format into a flat, ML-ready structure.
Overview
Data Source
The data comes from GTEx's snRNA-seq atlas:
Source: GTEx Portal
Publication: Eraslan et al., Science 2022 - "Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function"
Content: 209… See the full description on the dataset page: https://huggingface.co/datasets/ai-department-lpnu/gtex-single-cell-rnaseq.