ZIC2 and ZIC3 promote SWI/SNF recruitment to safeguard progression towards human primed pluripotency [RNA-seq]
RNA-seq (gene expression) · human · 38 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
- 38 samples: 38 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
- ZIC2 and ZIC3 promote SWI/SNF recruitment to safeguard progression towards human primed pluripotencyNature communications · 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 GSE270786_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 PRJNA1128169 and SRA study SRP516095. 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 38 sample titles: 38 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.
- GSM8352010 UCLA1 primed hESC, WT +sgNT, rep1 (RNA-seq)
- GSM8352011 UCLA1 primed hESC, WT +sgNT, rep2 (RNA-seq)
- GSM8352012 UCLA1 primed hESC, NT, rep1 (RNA-seq)
- GSM8352013 UCLA1 primed hESC, NT, rep2 (RNA-seq)
- GSM8352014 UCLA1 primed hESC, WT +sgZIC2, rep1 (RNA-seq)
- GSM8352015 UCLA1 primed hESC, WT +sgZIC2, rep2 (RNA-seq)
- GSM8352016 UCLA1 primed hESC, ZIC2-/- (RNA-seq)
- GSM8352017 UCLA1 primed hESC, ZIC3-/- +sgNT, rep1 (RNA-seq)
- GSM8352018 UCLA1 primed hESC, ZIC3-/- +sgNT, rep2 (RNA-seq)
- GSM8352019 UCLA1 primed hESC, ZIC3-/- +sgNT, rep3 (RNA-seq)
- GSM8352020 UCLA1 primed hESC, ZIC3-/- +sgNT, rep4 (RNA-seq)
- GSM8352021 UCLA1 primed hESC, ZIC5-/- +sgNT, rep1 (RNA-seq)
- GSM8352022 UCLA1 primed hESC, ZIC5-/- +sgNT, rep2 (RNA-seq)
- GSM8352023 UCLA1 primed hESC, ZIC5-/- +sgNT, rep3 (RNA-seq)
- GSM8352024 UCLA1 primed hESC, ZIC3-/- +sgZIC2, rep1 (RNA-seq)
- GSM8352025 UCLA1 primed hESC, ZIC3-/- +sgZIC2, rep2 (RNA-seq)
- GSM8352026 UCLA1 primed hESC, ZIC3-/- +sgZIC2, rep3 (RNA-seq)
- GSM8352027 UCLA1 primed hESC, ZIC3-/- +sgZIC2, rep4 (RNA-seq)
- GSM8352028 UCLA1 primed hESC, ZIC5-/- +sgZIC2, rep1 (RNA-seq)
- GSM8352029 UCLA1 primed hESC, ZIC5-/- +sgZIC2, rep2 (RNA-seq)
- GSM8352030 UCLA1 primed hESC, ZIC5-/- +sgZIC2, rep3 (RNA-seq)
- GSM8352031 UCLA1 primed hESC, ZIC3-/-ZIC5-/- +sgNT, rep1 (RNA-seq)
- GSM8352032 UCLA1 primed hESC, ZIC3-/-ZIC5-/- +sgNT, rep2 (RNA-seq)
- GSM8352033 UCLA1 primed hESC, ZIC3-/-ZIC5-/- +sgZIC2, rep1 (RNA-seq)
- GSM8352034 UCLA1 primed hESC, ZIC3-/-ZIC5-/- +sgZIC2, rep2 (RNA-seq)
- GSM8352035 UCLA1 primed hESC, ZIC3-/-ZIC5-/- +sgZIC2, rep3 (RNA-seq)
- GSM8352036 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, DMSO, rep1 (RNA-seq)
- GSM8352037 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, DMSO, rep2 (RNA-seq)
- GSM8352038 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, DMSO, rep3 (RNA-seq)
- GSM8352039 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, DMSO, rep4 (RNA-seq)
- GSM8352040 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, doxycycline 72h, rep1 (RNA-seq)
- GSM8352041 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, doxycycline 72h, rep2 (RNA-seq)
- GSM8352042 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, doxycycline 72h, rep3 (RNA-seq)
- GSM8352043 UCLA1 ZIC3-/- naïve hESC, inducible ZIC2, doxycycline 72h, rep4 (RNA-seq)
- GSM8352044 UCLA1 reverting hESC, NT, 5iLAF d6, rep1 (RNA-seq)
- GSM8352045 UCLA1 reverting hESC, NT, 5iLAF d6, rep2 (RNA-seq)
- GSM8352046 UCLA1 reverting hESC, ZIC3-/-, 5iLAF d6, rep1 (RNA-seq)
- GSM8352047 UCLA1 reverting hESC, ZIC3-/-, 5iLAF d6, rep2 (RNA-seq)
- GSE270787 ZIC2 and ZIC3 promote SWI/SNF recruitment to safeguard progression towards human primed pluripotency 205 samples shares zic2, zic3, swi, snf, pluripotency, recruitment, progression, safeguard
- GSE270784 ZIC2 and ZIC3 promote SWI/SNF recruitment to safeguard progression towards human primed pluripotency [ChIP-seq] 107 samples shares zic2, zic3, swi, snf, pluripotency, recruitment, progression, safeguard
- GSE270948 ZIC2 and ZIC3 promote SWI/SNF recruitment to safeguard progression towards human primed pluripotency [ATAC-Seq] 46 samples shares zic2, zic3, swi, snf, pluripotency, recruitment, progression, safeguard
- GSE180481 PHF6 cooperates with SWI/SNF complexes to facilitate transcriptional progression [RNA-seq] 38 samples shares swi, snf, progression
- GSE180487 PHF6 cooperates with SWI/SNF complexes to facilitate transcriptional progression 137 samples shares swi, snf, progression
- GSE180483 PHF6 cooperates with SWI/SNF complexes to facilitate transcriptional progression [ChIP-seq] 88 samples shares swi, snf, progression
- GSE261988 SWI/SNF is a gatekeeper of chromatin access at enhancer networks controlling triple-negative breast cancer progression [ChIP-Seq] 79 samples shares swi, snf, progression
- GSE299562 PHIP suppresses NuRD to enable the growth of SWI/SNF-mutant cancers [RNA-seq] 42 samples shares swi, snf
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.