Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD [ATAC-seq]
Single-cell RNA-seq · human · 31 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 31 samples: 22 distinct titles, 4 of them repeatedGroups 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
- GWAS-Informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral densitybioRxiv : the preprint server for biology · 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 GSE261280_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1086388 and SRA study SRP494464. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 31 sample titles: 22 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.
- GSM8139403 chondrocytes, extracted from knee articular cartilage, donor 1
- GSM8139404 chondrocytes, extracted from knee articular cartilage, donor 2
- GSM8139405 chondrocytes, extracted from knee articular cartilage, donor 3
- GSM8139406 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 1
- GSM8139407 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 2
- GSM8139408 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 3
- GSM8139409 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 1
- GSM8139410 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 2
- GSM8139411 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 3
- GSM8139412 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 4
- GSM8139413 hFOB 1.19, undifferentiated, rep 1
- GSM8139414 hFOB 1.19, undifferentiated, rep 2
- GSM8139415 hFOB 1.19, undifferentiated, rep 3
- GSM8139416 pediatric hMSC-osteoblasts, differentiated 3 days, 15 year-old, female, donor 1
- GSM8139417 pediatric hMSC-osteoblasts, differentiated 6 days, 15 year-old, female, donor 1
- GSM8139418 pediatric hMSCs, undifferentiated, 15 year-old, female, donor 1
- GSM8139419 pediatric hMSC-osteoblasts, differentiated 3 days, 18 year-old, male, donor 2
- GSM8139420 pediatric hMSC-osteoblasts, differentiated 6 days, 18 year-old, male, donor 2
- GSM8139421 pediatric hMSCs, undifferentiated, 18 year-old, male, donor 2
- GSM8139422 pediatric hMSC-osteoblasts, differentiated 3 days, 18 year-old, female, donor 3
- GSM8139423 pediatric hMSC-osteoblasts, differentiated 6 days, 18 year-old, female, donor 3
- GSM8139424 pediatric hMSCs, undifferentiated, 18 year-old, female, donor 3
- GSM8139425 pediatric hMSC-osteoblasts, differentiated 3 days, 16 year-old, female, donor 4
- GSM8139426 pediatric hMSC-osteoblasts, differentiated 6 days, 16 year-old, female, donor 4
- GSM8139427 pediatric hMSCs, undifferentiated, 16 year-old, female, donor 4
- GSM8139428 pediatric hMSC-osteoblasts, differentiated 3 days, 16 year-old, male, donor 5
- GSM8139429 pediatric hMSC-osteoblasts, differentiated 6 days, 16 year-old, male, donor 5
- GSM8139430 pediatric hMSCs, undifferentiated, 16 year-old, male, donor 5
- GSM8139431 pediatric hMSC-osteoblasts, differentiated 3 days, 17 year-old, male, donor 6
- GSM8139432 pediatric hMSC-osteoblasts, differentiated 6 days, 17 year-old, male, donor 6
- GSM8139433 pediatric hMSCs, undifferentiated, 17 year-old, male, donor 6
- GSE261284 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD 53 samples shares bmd, bioinformatics, crispri-based, multi-tissue, single-cell, implicates, effector, etiology
- GSE261283 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD [scCRISPR screen] 16 samples shares bmd, bioinformatics, crispri-based, multi-tissue, single-cell, implicates, effector, etiology
- GSE261282 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD [bulk RNA-seq] 3 samples shares bmd, bioinformatics, crispri-based, multi-tissue, single-cell, implicates, effector, etiology
- GSE261281 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD [Capture-C] 3 samples shares bmd, bioinformatics, crispri-based, multi-tissue, single-cell, implicates, effector, etiology
- 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 bmd
- GSE293846 Identification of known and novel long non-coding RNAs potentially responsible for the effects of BMD GWAS loci [hFOB RNA-seq] 18 samples shares bmd
- GSE201774 LINE-1 retrotransposons are reduced in bone of osteoporotic patients, correlate positively to BMD, and stimulate bone anabolism in transfected mesenchymal stem cells 16 samples shares bmd
- GSE340442 total RNA-seq from CD4-positive, alpha-beta T cell (ENCSR547BMD) 1 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.