Reversible epiblast regionalisation determines differentiation potential of human PSCs [RNA-Seq]
RNA-seq (gene expression) · human · 43 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 43 samples: 16 conditions, mostly in duplicateGroups 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.
Read the full summary ↓
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 GSE335881_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1479756 and SRA study SRP710704. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 32 samples.
How we read this: 16 replicated groups read from 43 sample titles; they account for 32 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.
- GSM9822458 Cuhk2_untreated_Rep1 Cuhk2_untreated
- GSM9822459 Cuhk2_untreated_Rep2 Cuhk2_untreated
- GSM9822460 Deyz2_untreated_Rep1 Deyz2_untreated
- GSM9822461 Deyz2_untreated_Rep2 Deyz2_untreated
- GSM9822462 H1_untreated_Rep1 H1_untreated
- GSM9822463 H1_untreated_Rep2 H1_untreated
- GSM9822464 H9_untreated_Rep1 H9_untreated
- GSM9822465 H9_untreated_Rep2 H9_untreated
- GSM9822466 Hehd1_CHR_Rep1 Hehd1_CHR
- GSM9822467 Hehd1_CHR_Rep2 Hehd1_CHR
- GSM9822468 Hehd1_untreated_Rep1 Hehd1_untreated
- GSM9822469 Hehd1_untreated_Rep2 Hehd1_untreated
- GSM9822470 HUES8_iCas9_untreated_Rep1 HUES8_iCas9_untreated
- GSM9822471 HUES8_iCas9_untreated_Rep2 HUES8_iCas9_untreated
- GSM9822472 Sojd3_CHR_Rep1 Sojd3_CHR
- GSM9822473 Sojd3_CHR_Rep2 Sojd3_CHR
- GSM9822474 Sojd3_untreated_Rep1 Sojd3_untreated
- GSM9822475 Sojd3_untreated_Rep2 Sojd3_untreated
- GSM9822476 Burb1_CHR_Rep1 Burb1_CHR
- GSM9822477 Burb1_CHR_Rep2 Burb1_CHR
- GSM9822478 Burb1_untreated_Rep1 Burb1_untreated
- GSM9822479 Burb1_untreated_Rep2 Burb1_untreated
- GSM9822480 Feec2_untreated_Rep1 Feec2_untreated
- GSM9822481 Feec2_untreated_Rep2 Feec2_untreated
- GSM9822482 Fiaj1_CHR_Rep1 Fiaj1_CHR
- GSM9822483 Fiaj1_CHR_Rep2 Fiaj1_CHR
- GSM9822484 Fiaj1_untreated_Rep1 Fiaj1_untreated
- GSM9822485 Fiaj1_untreated_Rep2 Fiaj1_untreated
- GSM9822486 Kolf2_untreated_Rep1 Kolf2_untreated
- GSM9822487 Kolf2_untreated_Rep2 Kolf2_untreated
- GSM9822488 Cuhk2_organoids_Day20
- GSM9822489 Deyz2_organoids_Day20
- GSM9822490 H1_organoids_Day20
- GSM9822491 H9_organoids_Day20
- GSM9822492 Hehd1_organoids_Day20
- GSM9822493 HUES8_organoids_Day20
- GSM9822494 Sojd3_organoids_Day20
- GSM9822495 Burb1_organoids_Day20
- GSM9822496 Feec2_organoids_Day20
- GSM9822497 Fiaj1_organoids_Day20
+ 3 more — browse all 43 samples with per-sample file links →
- GSE334577 Reversible epiblast regionalisation determines differentiation potential of human PSCs 141 samples shares regionalisation, reversible, determines, potential, epiblast, pscs
- GSE334112 Reversible epiblast regionalisation determines differentiation potential of human PSCs [ATAC-seq] 38 samples shares regionalisation, reversible, determines, potential, epiblast, pscs
- GSE299717 Human myeloid ontogeny drives differentiation potential in the brain environment [RNA-seq] 37 samples shares potential, rna-seq
- GSE272261 GABAergic neuronal lineage development determines clinically actionable targets in diffuse hemispheric glioma, H3G34-mutant [RNA-Seq] 57 samples shares determines, rna-seq
- GSE335924 RNA-seq Identifies FOS as a Potential Therapeutic Target Activating Neural Stem Cells via miR-21/SOX2 Pathway in Hypertensive Intracerebral Hemorrhage 53 samples shares potential, rna-seq
- GSE287953 Investigating therapy-induced senescence as a reversible escape mechanism of drug resistance in breast cancer cells using high-dose doxorubicin treatment [RNA-seq] 45 samples shares reversible, rna-seq
- GSE240411 Identification of potential targets of FTO in GIST via transcriptome-wide RNA-seq 24 samples shares potential, rna-seq
- GSE254808 Histone marks identify novel transcription factors that parse CAR-T cell subset-of-origin, clinical potential and expansion [RNA-seq] 18 samples shares potential, rna-seq
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.