Inorganic Ions Activate Lineage-Specific Gene Regulatory Networks to Drive Stem Cells Differentiation
RNA-seq (gene expression) · human · 15 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
- 15 samples: 6 conditions, mostly in triplicateGroups 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
- Inorganic ions activate lineage-specific gene regulatory networksActa biomaterialia · 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 GSE234727_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 PRJNA982823 and SRA study SRP442957. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 15 samples.
How we read this: 6 replicated groups read from 15 sample titles; they account for 15 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.
- GSM7473850 hMSCs 1 hMSCs
- GSM7473851 hMSCs 2 hMSCs
- GSM7473852 hMSCs Ag 1 hMSCs Ag
- GSM7473853 hMSCs Ag 2 hMSCs Ag
- GSM7473854 hMSCs Ag 3 hMSCs Ag
- GSM7473855 hMSCs Cu 1 hMSCs Cu
- GSM7473856 hMSCs Cu 2 hMSCs Cu
- GSM7473857 hMSCs Cu 3 hMSCs Cu
- GSM7473858 hMSCs Pt 1 hMSCs Pt
- GSM7473859 hMSCs Pt 2 hMSCs Pt
- GSM7473860 hMSCs Ta 1 hMSCs Ta
- GSM7473861 hMSCs Ta 2 hMSCs Ta
- GSM7473862 hMSCs Ta 3 hMSCs Ta
- GSM7473863 hMSCs Ti 1 hMSCs Ti
- GSM7473864 hMSCs Ti 2 hMSCs Ti
- GSE319266 Identification of target genes and regulatory networks for bone mineral density GWAS loci through systematic targeting and inhibition [hFOB BMD STING-seq] 24 samples shares regulatory, networks, stem
- GSE278330 Systemic IL-23 blockade downregulates IL-23 receptor-expressing Type 17 T-cell subsets and upregulates regulatory gene expression in myeloid cells in human psoriasis skin 63 samples shares regulatory, stem
- GSE314625 WSTF deficiency reprograms regulatory networks by linking locus‑specific chromatin remodeling to altered isoform expression and misdirected signaling [mRNA-seq] 18 samples shares regulatory, networks
- GSE309709 Three immunoregulatory signatures define non-productive HIV infection in stem cell memory CD4+ T cells 16 samples shares regulatory, stem
- GSE299831 KOLF2.1J iTF-Microglia: A standardized platform to study microglial transcriptional regulatory networks in CNS disease [RNA-seq] 12 samples shares regulatory, networks
- GSE297914 PU.1-Activated Genomic Regions Define Low-risk MDS Subsets Characterized by Immune Dysregulation and Disease Progression [ChIP-seq] 112 samples shares activate, ions
- GSE303901 An unbiased survey of distal element-gene regulatory interactions with direct-capture targeted Perturb-seq 97 samples shares regulatory, ions
- GSE281576 Long-range enhancer-controlled genes are hyper-sensitive to regulatory factor perturbations 54 samples shares regulatory, ions
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.