Multiplex generation and single cell analysis of structural variants in mammalian genomes
Single-cell RNA-seq · human · 197 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
- 197 samples: 31 conditions, mostly in duplicateGroups 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
- Multiplex generation and single-cell analysis of structural variants in mammalian genomesScience (New York, N.Y.) · 2025
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 GSE282636_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 PRJNA1189508 and SRA study SRP547022. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 150 samples.
How we read this: 31 replicated groups read from 197 sample titles; they account for 150 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.
- GSM8647676 parental_rep1 parental
- GSM8647677 4ugCre_d3_rep1 4ugCre_d3
- GSM8647678 1ugCre_d3_rep1 1ugCre_d3
- GSM8647679 200ngCre_d3_rep1 200ngCre_d3
- GSM8647680 4ugBxb1_d3_rep1 4ugBxb1_d3
- GSM8647681 1ugBxb1_d3_rep1 1ugBxb1_d3
- GSM8647682 200ngBxb1_d3_rep1 200ngBxb1_d3
- GSM8647683 parental_rep2 parental
- GSM8647684 4ugCre_d3_rep2 4ugCre_d3
- GSM8647685 1ugCre_d3_rep2 1ugCre_d3
- GSM8647686 200ngCre_d3_rep2 200ngCre_d3
- GSM8647687 4ugBxb1_d3_rep2 4ugBxb1_d3
- GSM8647688 1ugBxb1_d3_rep2 1ugBxb1_d3
- GSM8647689 200ngBxb1_d3_rep2 200ngBxb1_d3
- GSM8647690 parental_rep3 parental
- GSM8647691 parental_rep4 parental
- GSM8647692 CreERT2_Tamoxifen_d3_rep1
- GSM8647693 ERT2CreERT2_Tamoxifen_d3_rep1
- GSM8647694 Cre_NoTamoxifen_d3_rep1
- GSM8647695 CreERT2_NoTamoxifen_d3_rep1
- GSM8647696 ERT2CreERT2_NoTamoxifen_d3_rep1
- GSM8647697 CreERT2_Tamoxifen_d5_rep1
- GSM8647698 ERT2CreERT2_Tamoxifen_d5_rep1
- GSM8647699 Cre_NoTamoxifen_d5_rep1
- GSM8647700 CreERT2_NoTamoxifen_d5_rep1
- GSM8647701 ERT2CreERT2_NoTamoxifen_d5_rep1
- GSM8647702 CreERT2_Tamoxifen_d7_rep1
- GSM8647703 ERT2CreERT2_Tamoxifen_d7_rep1
- GSM8647704 Cre_NoTamoxifen_d7_rep1
- GSM8647705 CreERT2_NoTamoxifen_d7_rep1
- GSM8647706 ERT2CreERT2_NoTamoxifen_d7_rep1
- GSM8647707 Cre_Pifi48h-at24h_d3_rep1
- GSM8647708 Cre_NoPifi_d3_rep1
- GSM8647709 Cre_Pifi48h-at24h_d5_rep1
- GSM8647710 Cre_NoPifi_d5_rep1
- GSM8647711 Shuffle_clone_A1 Shuffle_clone_A
- GSM8647712 Shuffle_clone_B1 Shuffle_clone_B
- GSM8647713 Shuffle_clone_C1 Shuffle_clone_C
- GSM8647714 Shuffle_clone_D1 Shuffle_clone_D
- GSM8647715 Shuffle_clone_E1 Shuffle_clone_E
+ 157 more — browse all 197 samples with per-sample file links →
- GSE282634 Multiplex generation and single cell analysis of structural variants in mammalian genomes [scRNA-seq] 8 samples shares generation, structural, multiplex, mammalian, variants, genomes
- GSE35156 Conserved Topological Domains in Mammalian Genomes Identified by High-resolution Analysis of Chromatin Interactions 9 samples shares mammalian, genomes
- GSE271398 The RNA binding protein Bcas2 is necessary for antibody class switch in mammalian genomes 14 samples shares mammalian, genomes
- GSE238093 Loss of an oligodendrocyte specific silencer element provides a framework to assess the pathogenic impact of lamin B1 structural variants 7 samples shares structural, variants
- GSE97179 Single Cell Methylome Signatures Reveal Distinct Neuronal Populations and Regulatory Elements in the Mammalian Cortex 6172 samples shares mammalian
- GSE288933 Pervasive and programmed nucleosome distortion patterns on single mammalian chromatin fibers 162 samples shares mammalian
- GSE300551 Massively multiplex multi-modal chemical screens at single-cell resolution with icCITE-plex 25 samples shares multiplex
- GSE248942 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (ATAC-Seq) 123 samples shares generation
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.