Single-cell multi-omics profiling of PBMCs from SLE patients pre- and post-dual-target (BCMA/CD19) CAR-T therapy
Single-cell RNA-seq · human · 30 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
- 30 samples: 30 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.
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 GSE304878_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 PRJNA1303131 and SRA study SRP607417. 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 30 sample titles: 30 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.
- GSM9158907 Patient1, POST1, scRNA
- GSM9158908 Patient1, PRE1, scRNA
- GSM9158909 Patient2, POST2, scRNA
- GSM9158910 Patient2, PRE2, scRNA
- GSM9158911 Patient3, POST3, scRNA
- GSM9158912 Patient3, PRE3, scRNA
- GSM9158913 Patient4, POST4, scRNA
- GSM9158914 Patient4, PRE4, scRNA
- GSM9158915 Patient5, POST5, scRNA
- GSM9158916 Patient5, PRE5, scRNA
- GSM9158917 Patient1, POST1, BCR
- GSM9158918 Patient1, PRE1, BCR
- GSM9158919 Patient2, POST2, BCR
- GSM9158920 Patient2, PRE2, BCR
- GSM9158921 Patient3, POST3, BCR
- GSM9158922 Patient3, PRE3, BCR
- GSM9158923 Patient4, POST4, BCR
- GSM9158924 Patient4, PRE4, BCR
- GSM9158925 Patient5, POST5, BCR
- GSM9158926 Patient5, PRE5, BCR
- GSM9158927 Patient1, POST1, TCR
- GSM9158928 Patient1, PRE1, TCR
- GSM9158929 Patient2, POST2, TCR
- GSM9158930 Patient2, PRE2, TCR
- GSM9158931 Patient3, POST3, TCR
- GSM9158932 Patient3, PRE3, TCR
- GSM9158933 Patient4, POST4, TCR
- GSM9158934 Patient4, PRE4, TCR
- GSM9158935 Patient5, POST5, TCR
- GSM9158936 Patient5, PRE5, TCR
- GSE322796 Persistence of mucosal CAR-T cells and inflammatory remodeling in enterocolitis associated with BCMA CAR-T cell therapy 23 samples shares car-t, bcma, therapy
- GSE274187 CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy 23 samples shares car-t, bcma, therapy
- GSE246342 CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy I 18 samples shares car-t, bcma, therapy
- GSE271915 Reconstitution of the Multiple Myeloma Microenvironment Following Lymphodepletion with BCMA CAR-T Therapy 14 samples shares car-t, bcma, therapy
- GSE335464 Integrative single-cell multi-omics profiling of human pancreatic islets identifies T1D-associated genes and regulatory signals [single cell] 28 samples shares sle, single-cell, multi-omics
- GSE263931 Selective CAR-T cell mediated B cell depletion suppresses interferon signature in SLE [PBMC] 28 samples shares car-t, sle
- GSE263932 Selective CAR-T cell mediated B cell depletion suppresses interferon signature in SLE [Bcells] 20 samples shares car-t, sle
- GSE231429 Placental T cells retain enhanced stemness and altered cytokine response favoring durable efficacy of CD19 CAR-T 13 samples shares car-t, cd19
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.