Human hypothalamus-pituitary organoids — differentiation outcome
Homo sapiens · Whole hypothalamus · bulk RNA-seq
Selected data and study scope
This dataset contains bulk RNA-seq data from Homo sapiens, sampled from whole hypothalamus. The default comparison examines gene expression in Predicted differentiation success relative to Predicted differentiation failure.
The data come from day-15 human iPSC-derived hypothalamus-pituitary organoid cultures. The comparison groups cultures by the study's machine-learning predictions of successful or unsuccessful differentiation. It excludes day-9 libraries to keep the sampled timepoint consistent.
The explorer includes 1 track and 1 comparison for this dataset.
The default track, Hypothalamus-pituitary organoid, includes 4 Predicted differentiation failure samples and 4 Predicted differentiation success samples in this comparison. These are analysis sample counts. Check the source for biological replication and pooling.
Interpretation and limitations
The group labels describe predicted differentiation outcomes. This comparison uses cultured organoids, not human hypothalamic tissue. The source-count analysis shown here excludes two synthetic reporter rows.
These data come from a cell-culture model. Check the cell line or differentiation system and the conditions sampled before interpreting a result.
Expression values are CPM (TMM-normalized): counts per million on library sizes adjusted by the TMM factors of the study’s own edgeR fit. This scale adjusts for library size and composition, not gene length. Use it to inspect a feature across the samples in this analysis. CPM values are not absolute transcript counts.
Evidence and verification
Pipeline QC passed. Human hypothalamus-pituitary organoids — differentiation outcome; all 1 registered contrasts on default track organoid
Experimental design review needed. Human hypothalamus-pituitary organoids — differentiation outcome; all 1 registered contrasts on default track organoid
Author concordance passed. Selected author genes only; success_vs_failure_day15. P values and FDR are contextual. Numerical acceptance: strong correlation and matched-gene direction.
Pipeline QC can pass while experimental-design limitations remain. Read both assessments before interpreting results.
Open the dataset in the Explorer to read each check and its evidence. Author concordance compares effects for matched genes. It does not require identical author P values or FDR.
Read the analysis methods and interpretation guide and how to cite the source study and HypoExplorer. The source publication may include tissues, groups or comparisons beyond the data shown here.
Source study
Day-15 hiPSC-derived hypothalamus-pituitary-organoid RNA-seq comparing four machine-learning-predicted successful with four failed differentiations. Day-9 libraries are excluded to avoid timepoint mixing, and two synthetic reporter rows are quarantined from the official HTSeq counts (PMID 40763741; GSE301692)
Source publication
Prediction of the hypothalamus-pituitary organoid formation using machine learning.
Matsumoto R, Suga H, Takahashi Y, Aoi T, Yamamoto T
Cell reports methods · 2025
Repository study title
Global transcriptional profiles of hiPSC-derived hypothalamus-pituitary organoids predicted to fail or succeed by machine learning model
The original study authors produced these data. HypoExplorer displays selected data and analyses that may cover only part of the study.
Comparisons in HypoExplorer
Predicted differentiation success vs Predicted differentiation failure · default
Positive differential-expression values indicate higher expression in the case group relative to the baseline. Check the comparison direction and study design when interpreting results.
Available tracks
| Track | Features | Predicted differentiation failure n | Predicted differentiation success n |
|---|---|---|---|
| Hypothalamus-pituitary organoid | 15,416 | 4 | 4 |
Expression and analysis results
Open this dataset to inspect gene expression and differential-expression results across the available tracks. Pathway enrichment is also available. The pathway databases differ by dataset.
HypoExplorer is in beta testing. Features and analyses may change during testing. Review the original source, analysis methods and quality-control checks before using a result in research.