This collection lists hypothalamic datasets generated with single-cell RNA-seq or single-nucleus RNA-seq. Check both the source assay and the analysis available in HypoExplorer. The macaque atlas has individual population tracks, whereas the mouse studies listed below are aggregated to one expression profile per animal for the selected comparison.
Use the macaque atlas to browse population-specific obese-versus-normal results. Choose a mouse entry when its species, region, developmental stage and intervention fit your question. The app aggregates mouse data by animal, so the available results may not include the original cell annotations or embeddings.
Wenyuan He created HypoExplorer and holds a PhD from the University of Toronto. About the author.
Cells from one animal do not constitute independent animals. In the mouse pseudobulk views, deposited cells and within-animal technical runs are combined before the selected group comparison. Use the biological sample count on the study page when assessing replication.
GSE143818 captures developing VMH Sf1-lineage cells and GSE174085 captures PVN CRH-expressing cells. Their animal-level aggregates are lineage-enriched comparisons, not interchangeable whole-hypothalamus estimates. The GSE130597 analysis combines captured LHA cell types because the public data lack a barcode-to-cell-type map.
P0 arcuate-median-eminence data, P10 VMH-lineage cells and adult whole-hypothalamus data differ in age and sampled cells. This guide excludes sorted bulk RNA-seq, TRAP, RiboTag and spatial RNA-seq, even when they target a cell type. Follow each source citation for the original atlas scope and the study page for the subset used in HypoExplorer.
The macaque dataset lets you browse populations in the explorer.
Macaca fascicularis · snRNA-seq · Whole hypothalamus
Baseline → case: Normal → Obese
Cynomolgus macaque hypothalamus, normal versus obese, across 60 population tracks. This is an obese-versus-normal reanalysis of the Lei et al. atlas, with the source authors credited separately.
Each entry identifies the source assay and states how the data are aggregated. Open a study for its biological sample counts, comparison direction and caveats.
Mus musculus · scRNA-seq · Lateral hypothalamus
Baseline → case: Control chow → High-fat diet
Lateral hypothalamus, control chow versus HFD. The captured cells are aggregated by mouse with sequencing pool modeled; no public barcode-to-cell-type map is available.
Mus musculus · scRNA-seq · Whole hypothalamus
Baseline → case: Normal fed → Food deprived (24 h)
Whole hypothalamus, normal feeding versus 24-hour food deprivation. Seventeen technical partitions are collapsed to eight independent mouse pseudobulks.
Mus musculus · scRNA-seq · Whole hypothalamus
Baseline → case: Fructose control → Fructose + A. muciniphila
Fructose-fed mouse hypothalamus with or without Akkermansia muciniphila, aggregated to three animal libraries per arm. The cited source is a preprint.
Mus musculus · scRNA-seq · Ventromedial hypothalamus
Baseline → case: Female (P10) → Male (P10)
P10 VMH Sf1-lineage cells, female versus male, aggregated by mouse. This is a developmental lineage-enriched view, not an adult whole-hypothalamus estimate.
Mus musculus · scRNA-seq · Paraventricular nucleus
Baseline → case: Control rearing → Early-life adversity
P10 to P12 PVN CRH-expressing cells, control rearing versus early-life adversity; cells are aggregated by animal and collection age is modeled.
Mus musculus · scRNA-seq · Arcuate nucleus
Baseline → case: Control → Mettl14 KO
P0 arcuate-median-eminence cells, control versus Mettl14 knockout. Sections and droplet runs are pooled within each animal to form eight mouse pseudobulks.
These guides share some of the same datasets and explain how to use them for other research questions.
This guide selects studies by the comparisons and assays available in HypoExplorer. It does not combine results into a meta-analysis. Each study page credits the original authors and describes the subset shown in the app.
Follow the gene-search instructions to inspect a gene, or the data and export guide to save results. Read the analysis methods and limitations before interpreting a result. Use the citation guide to credit the original researchers and this app.