Identification of target genes and regulatory networks for bone mineral density GWAS loci through systematic targeting and inhibition [hFOB BMD STING-seq]
RNA-seq (gene expression) · human · 24 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
- 24 samples: 6 conditions, mostly with about 6 replicates eachGroups 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
- Identification of target genes and regulatory networks for bone mineral density GWAS loci through systematic targeting and inhibitionbioRxiv : the preprint server for biology · 2026
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 GSE319266_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 PRJNA1422730 and SRA study SRP676553. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 24 samples.
How we read this: 6 replicated groups read from 24 sample titles; they account for 24 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.
- GSM9514430 BMD STING-seq pilot cDNA 1 BMD STING-seq pilot cDNA
- GSM9514431 BMD STING-seq pilot HTO 1 BMD STING-seq pilot HTO
- GSM9514432 BMD STING-seq pilot GDO 1 BMD STING-seq pilot GDO
- GSM9514433 BMD STING-seq pilot cDNA 2 BMD STING-seq pilot cDNA
- GSM9514434 BMD STING-seq pilot HTO 2 BMD STING-seq pilot HTO
- GSM9514435 BMD STING-seq pilot GDO 2 BMD STING-seq pilot GDO
- GSM9514436 BMD STING-seq full cDNA 1 BMD STING-seq full cDNA
- GSM9514437 BMD STING-seq full HTO 1 BMD STING-seq full HTO
- GSM9514438 BMD STING-seq full GDO 1 BMD STING-seq full GDO
- GSM9514439 BMD STING-seq full cDNA 2 BMD STING-seq full cDNA
- GSM9514440 BMD STING-seq full HTO 2 BMD STING-seq full HTO
- GSM9514441 BMD STING-seq full GDO 2 BMD STING-seq full GDO
- GSM9514442 BMD STING-seq full cDNA 3 BMD STING-seq full cDNA
- GSM9514443 BMD STING-seq full HTO 3 BMD STING-seq full HTO
- GSM9514444 BMD STING-seq full GDO 3 BMD STING-seq full GDO
- GSM9514445 BMD STING-seq full cDNA 4 BMD STING-seq full cDNA
- GSM9514446 BMD STING-seq full HTO 4 BMD STING-seq full HTO
- GSM9514447 BMD STING-seq full GDO 4 BMD STING-seq full GDO
- GSM9514448 BMD STING-seq full cDNA 5 BMD STING-seq full cDNA
- GSM9514449 BMD STING-seq full HTO 5 BMD STING-seq full HTO
- GSM9514450 BMD STING-seq full GDO 5 BMD STING-seq full GDO
- GSM9514451 BMD STING-seq full cDNA 6 BMD STING-seq full cDNA
- GSM9514452 BMD STING-seq full HTO 6 BMD STING-seq full HTO
- GSM9514453 BMD STING-seq full GDO 6 BMD STING-seq full GDO
- GSE280280 Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory circuits During Response to MAPK Inhibition in BRAF-mutant colorectal cancer 36 samples shares regulatory, inhibition
- GSE299850 KOLF2.1J iTF-Microglia: A standardized platform to study microglial transcriptional regulatory networks in CNS disease 36 samples shares regulatory, networks
- 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
- GSE234727 Inorganic Ions Activate Lineage-Specific Gene Regulatory Networks to Drive Stem Cells Differentiation 15 samples shares regulatory, networks
- GSE299831 KOLF2.1J iTF-Microglia: A standardized platform to study microglial transcriptional regulatory networks in CNS disease [RNA-seq] 12 samples shares regulatory, networks
- GSE301119 Integrative analysis of pooled CRISPR screens provide functional insights into AD GWAS risk genes 28 samples shares gwas
- GSE263804 Chromatin accessibility mapping for functional GWAS risk variants of neuropsychiatric and neurodegenerative disorders in hiPSC-derived neural cells 141 samples shares gwas
- GSE261284 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD 53 samples shares bmd
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.