Spatiotemporal transcriptomic changes of human ovarian aging and the key regulatory role of FOXP1
Single-cell RNA-seq · human · 24 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 24 samples: 24 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Spatiotemporal transcriptomic changes of human ovarian aging and the regulatory role of FOXP1Nature aging · 2024
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE255690_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1075210 and SRA study SRP489224. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8077816 Ovary,young-1,scRNAseq
- GSM8077817 Ovary,young-3,scRNAseq
- GSM8077818 Ovary,young-4,scRNAseq
- GSM8077819 Ovary,middle-2,scRNAseq
- GSM8077820 Ovary,middle-3,scRNAseq
- GSM8077821 Ovary,middle-4,scRNAseq
- GSM8077822 Ovary,old-1,scRNAseq
- GSM8077823 Ovary,old-2,scRNAseq
- GSM8077824 Ovary,old-3,scRNAseq
- GSM8077825 Ovary,young-1,spatial
- GSM8077826 Ovary,young-2,spatial
- GSM8077827 Ovary,young-3,spatial
- GSM8077828 Ovary,young-4,spatial
- GSM8077829 Ovary,young-5,spatial
- GSM8077830 Ovary,middle-1,spatial
- GSM8077831 Ovary,middle-2,spatial
- GSM8077832 Ovary,middle-3,spatial
- GSM8077833 Ovary,middle-4,spatial
- GSM8077834 Ovary,middle-5,spatial
- GSM8077835 Ovary,old-1,spatial
- GSM8077836 Ovary,old-2,spatial
- GSM8077837 Ovary,old-3,spatial
- GSM8077838 Ovary,old-4,spatial
- GSM8077839 Ovary,old-5,spatial
- GSE268599 Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease 146 samples shares spatiotemporal, changes
- GSE330029 Temporal changes in metabolism guide oligodendrocyte precursor cell dynamics in aging and multiple sclerosis [BulkRNAseq] 108 samples shares changes, aging
- GSE282532 Transcriptomic changes in paired eutopic and ectopic endometrium of ovarian endometriosis 10 samples shares changes, ovarian
- GSE298243 Single-Cell Profiling of DNA Methylation in Autism Spectrum Disorder Prefrontal Cortex Reveals Distinct Regulatory and Aging Signatures 49 samples shares regulatory, aging
- GSE280555 Postbiotic derived from Lactobacillus paracasei CNCM I-5220 as a novel approach to improve aging-induced skin changes 21 samples shares changes, aging
- GSE247982 The chromatin landscape of high-grade serous ovarian cancer metastasis identifies potential regulatory drivers of chemoresistant tumour cells 10 samples shares regulatory, ovarian
- GSE276133 Integrative epigenomic profiling of hepatocellular carcinoma uncovers aberrant cis-regulatory changes and potential prognostic indicators [RNA-seq] 10 samples shares regulatory, changes
- GSE224689 Regulatory principles of human mitochondrial gene expression revealed by kinetic analysis of the RNA life cycle. 113 samples shares regulatory
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.