Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD
Single-cell RNA-seq · human · 53 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
- 53 samples: 7 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
- 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 GSE261284_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 PRJNA1086383 and SRA study SRP494461. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 35 samples.
How we read this: 7 replicated groups read from 53 sample titles; they account for 35 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.
- GSM8139403 chondrocytes, extracted from knee articular cartilage, donor 1 chondrocytes, extracted…
- GSM8139404 chondrocytes, extracted from knee articular cartilage, donor 2 chondrocytes, extracted…
- GSM8139405 chondrocytes, extracted from knee articular cartilage, donor 3 chondrocytes, extracted…
- GSM8139406 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 1 In-vitro differentiated…
- GSM8139407 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 2 In-vitro differentiated…
- GSM8139408 In-vitro differentiated osteoclasts, differentiated for 4 days with RANKL, donor 3 In-vitro differentiated…
- GSM8139409 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 1 hFOB 1.19, differentiat…
- GSM8139410 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 2 hFOB 1.19, differentiat…
- GSM8139411 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 3 hFOB 1.19, differentiat…
- GSM8139412 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep 4 hFOB 1.19, differentiat…
- GSM8139413 hFOB 1.19, undifferentiated, rep 1 hFOB 1.19, undifferenti…
- GSM8139414 hFOB 1.19, undifferentiated, rep 2 hFOB 1.19, undifferenti…
- GSM8139415 hFOB 1.19, undifferentiated, rep 3 hFOB 1.19, undifferenti…
- 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
- GSM8139434 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep1 hFOB 1.19, differentiat…
- GSM8139435 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep2 hFOB 1.19, differentiat…
- GSM8139436 hFOB 1.19, differentiated 5 days at 39.5⁰C, rep3 hFOB 1.19, differentiat…
- GSM8139437 RNA-seq_hFOB 1.19, differentiated 5 days at 39.5⁰C, rep1 RNA-seq_hFOB 1.19, diff…
- GSM8139438 RNA-seq_hFOB 1.19, differentiated 5 days at 39.5⁰C, rep2 RNA-seq_hFOB 1.19, diff…
- GSM8139439 RNA-seq_hFOB 1.19, differentiated 5 days at 39.5⁰C, rep3 RNA-seq_hFOB 1.19, diff…
- GSM8139440 GDO_hFOB 1.19, transfected with custom CRISPRi sgRNA pool 1 GDO_hFOB 1.19, transfec…
- GSM8139441 GDO_hFOB 1.19, transfected with custom CRISPRi sgRNA pool 2 GDO_hFOB 1.19, transfec…
- GSM8139442 GDO_hFOB 1.19, transfected with custom CRISPRi sgRNA pool 3 GDO_hFOB 1.19, transfec…
+ 13 more — browse all 53 samples with per-sample file links →
- GSE261280 Bioinformatics and single-cell CRISPRi-based screen reveals effector genes and implicates multi-tissue etiology for BMD [ATAC-seq] 31 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
- GSE85011 CRISPRi-based genome-scale identification of functional long non-coding RNA loci in human cells 112 samples shares crispri-based
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.