Endogenous Nodal switches Wnt interpretation from posteriorization to germ layer differentiation in geometrically constrained human pluripotent cells
RNA-seq (gene expression) · human · 12 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
- 12 samples: 5 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.
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 GSE263291_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 PRJNA1096648 and SRA study SRP499947. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 5 replicated groups read from 12 sample titles; they account for 10 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.
- GSM8189196 Control, rep 1 Control,
- GSM8189197 WNT 1x, SOX2 negative, rep1 WNT 1x, SOX2 negative,
- GSM8189198 WNT 1x, SOX2 positive, rep1 WNT 1x, SOX2 positive,
- GSM8189199 WNT 3x, SOX2 negative, rep 1
- GSM8189200 WNT 3x, SOX2 positive, rep 1
- GSM8189201 WNT 10x, SOX2 negative, rep 1 WNT 10x, SOX2 negative,
- GSM8189202 WNT 10x, SOX2 positive, rep 1 WNT 10x, SOX2 positive,
- GSM8189203 Control, rep 2 Control,
- GSM8189204 WNT 1x, SOX2 negative, rep2 WNT 1x, SOX2 negative,
- GSM8189205 WNT 1x, SOX2 positive, rep2 WNT 1x, SOX2 positive,
- GSM8189206 WNT 10x, SOX2 negative, rep 2 WNT 10x, SOX2 negative,
- GSM8189207 WNT 10x, SOX2 positive, rep 2 WNT 10x, SOX2 positive,
- GSE263335 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [STARR-RNA-seq] 16 samples shares interpretation
- GSE316724 Deep mutational scanning of CHD2 for variant interpretation in neurodevelopmental disorders [RNA-seq] 16 samples shares interpretation
- GSE267549 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [wt RNA-seq] 2 samples shares interpretation
- GSE252104 Scalable production of uniform and mature organoids in a 3D geometrically-engineered permeable membrane 2 samples shares geometrically
- GSE263337 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [ChIP-seq] 16 samples shares interpretation
- GSE263336 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [plasmid DNA-seq] 4 samples shares interpretation
- GSE263338 A functional genomics atlas enhanced by convolutional neural networks facilitates clinical interpretation of disease relevant variants in non-coding regulatory elements [ATAC-seq] 4 samples shares interpretation
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.