Mapping genotypes to chromatin accessibility profiles in single cells
Single-cell RNA-seq · human · 55 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
- 55 samples: 55 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
- Mapping genotypes to chromatin accessibility profiles in single cellsNature · 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 GSE204912_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 PRJNA842707 and SRA study SRP375854. 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 55 sample titles: 55 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.
- GSM6165291 SM4 [ATAC-seq]
- GSM6165292 RM30 [ATAC-seq]
- GSM6165293 Pt-01 (PV) [ATAC-seq]
- GSM6165294 Pt-01 (MF-T0) [ATAC-seq]
- GSM6165295 Pt-02 [ATAC-seq]
- GSM6165296 Pt-03 [ATAC-seq]
- GSM6165297 Pt-04 [ATAC-seq]
- GSM6165298 Pt-01 (MF-T1) [ATAC-seq]
- GSM6165299 Pt-05 [ATAC-seq]
- GSM6165300 Pt-06 [ATAC-seq]
- GSM6165301 Pt-07 [ATAC-seq]
- GSM6165302 Pt-02 (GoT-ChA-ASAP) [ATAC-seq]
- GSM6165303 Pt-06 (GoT-ChA-ASAP) [ATAC-seq]
- GSM6202211 SM4 [Genotyping GoT-ChA amplicon]
- GSM6202212 RM30 [Genotyping GoT-ChA amplicon]
- GSM6202213 Pt-01 (PV) [Genotyping GoT-ChA amplicon]
- GSM6202214 Pt-01 (MF-T0) [Genotyping GoT-ChA amplicon]
- GSM6202215 Pt-02 [Genotyping GoT-ChA amplicon]
- GSM6202216 Pt-03 [Genotyping GoT-ChA amplicon]
- GSM6202217 Pt-04 [Genotyping GoT-ChA amplicon]
- GSM6202218 Pt-01 (MF-T1) [Genotyping GoT-ChA amplicon]
- GSM6202219 Pt-05 [Genotyping GoT-ChA amplicon]
- GSM6202220 Pt-06 [Genotyping GoT-ChA amplicon]
- GSM6202221 Pt-07 [Genotyping GoT-ChA amplicon]
- GSM6202222 Pt-02 (GoT-ChA-ASAP) [Genotyping GoT-ChA amplicon]
- GSM6202223 Pt-06 (GoT-ChA-ASAP) [Genotyping GoT-ChA amplicon]
- GSM7887612 Multiplexing_original_protocol
- GSM7887613 Multiplexing_adapted
- GSM7887614 Pt-08 [ATAC-seq]
- GSM7887615 Pt-09 [ATAC-seq]
- GSM7887616 Pt-10 [ATAC-seq]
- GSM7887617 Pt-11 [ATAC-seq]
- GSM7887618 Pt-12
- GSM7887619 Pt-13 [ATAC-seq]
- GSM7887620 Pt-14 [ATAC-seq]
- GSM7887621 Pt-15 [ATAC-seq]
- GSM7887622 Pt-16 [ATAC-seq]
- GSM7887623 Pt-17 [ATAC-seq]
- GSM7887624 Pt-18 [ATAC-seq]
- GSM7887625 Pt-19 [ATAC-seq]
+ 15 more — browse all 55 samples with per-sample file links →
- GSE204911 Mapping genotypes to chromatin accessibility profiles in single cells [Genotyping GoT-ChA amplicon] 27 samples shares accessibility, genotypes, chromatin, profiles, mapping
- GSE256207 Accessible chromatin profiles (ATAC) at single-cell level of human post-mortem brain tissue from the orbitofrontal cortex 92 samples shares chromatin, profiles
- GSE244585 Single nuclei chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry [10X single-cell multiome] 32 samples shares accessibility, chromatin
- GSE278910 Pooled CRISPR screens with joint single-nucleus chromatin accessibility and transcriptome profiling [CUT&RUN] 30 samples shares accessibility, chromatin
- GSE287902 BPTF regulstes androgen receptor activity by enhancing chromatin accessibility and stabilizing the AR-FOXA1 interaction [Cut&Run] 40 samples shares accessibility, chromatin
- GSE316389 Chromatin accessibility and gene expression profiling of primary and metastatic ER+ breast cancer [ATAC-seq] 36 samples shares accessibility, chromatin
- GSE325835 BATF3 regulates chromatin accessibility during CD8+ T lymphocyte differentiation 36 samples shares accessibility, chromatin
- GSE316391 Chromatin accessibility and gene expression profiling of primary and metastatic ER+ breast cancer [RNA-seq] 32 samples shares accessibility, chromatin
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.