Single cell RNA-sequencing of H9 human embryonic stem cell-derived cortical organoid slice cultures (ALI-COs) at various timepoints
Single-cell RNA-seq · human · 10 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 10 samples: 3 × H9DIV150 vs 3 × H9DIV290 vs 2 × H9DIVGroups 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.
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 GSE254260_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 PRJNA1069092 and SRA study SRP485986. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 3 replicated groups read from 10 sample titles; they account for 8 of them. 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.
- GSM8036884 H9DIV100 H9DIV
- GSM8036885 H9DIV150_1 H9DIV150
- GSM8036886 H9DIV150_2 H9DIV150
- GSM8036887 H9DIV150_3 H9DIV150
- GSM8036888 H9DIV290_1 H9DIV290
- GSM8036889 H9DIV290_2 H9DIV290
- GSM8036890 H9DIV290_3 H9DIV290
- GSM8036891 H9DIV360 H9DIV
- GSM8036892 H9DIV390_B
- GSM8036893 H9DIV390_A
- GSE249826 Human-induced pluripotent Stem Cell-Derived Hepatic Stellate Cells in Liver Organoids: Maturation Promotion and Essential Role in Vascularization 26 samples shares cell-derived, organoid
- GSE268981 Graphene-polymer nanofibers enable optically induced electrical maturation in stem cell-derived cardiomyocytes and brain organoids 23 samples shares cell-derived, organoid
- GSE305933 Temporal multi-omics gene expression data across human embryonic stem cell-derived polyhormonal cell differentiation [RNA-seq] 20 samples shares cell-derived, embryonic
- GSE326655 in vivo human embryonic spinal cord atlas validates stem cell-derived human dorsal interneurons and reveals ASD spinal signatures [day43NMP_scRNAseq] 12 samples shares cell-derived, embryonic
- GSE262419 Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes 4558 samples shares cell-derived
- GSE300470 A Stem and Progenitor Cell-Derived Gene Expression Signature is Prognostic for Survival in Myelofibrosis [RNA-Seq] 358 samples shares cell-derived
- GSE240656 Multi-center Korean cohort study based on RNA-sequencing data targeting COPD patients 294 samples shares rna-sequencing
- GSE184487 RNA-sequencing of PBMC cultured with PolyI:C or LPS, from a pediatric cohort who received OM85 or placebo. 193 samples shares rna-sequencing
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.