Single cell transcriptomic data of 12 samples collected from twins with Multicentric Castleman Disease and an unaffected sibling
Single-cell RNA-seq · human · 12 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
- 12 samples: 12 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
- Single-cell landscape of idiopathic multicentric Castleman disease in identical twinsBlood · 2024
Read the full summary ↓
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 GSE241096_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 PRJNA1006396 and SRA study SRP455668. 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 12 sample titles: 12 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.
- GSM7716382 Bone Marrow of CS3392
- GSM7716383 PBMC of CM3391 on 6Dec21
- GSM7716384 PBMC of CS3392 on 10Nov20
- GSM7716385 PBMC of CS3392 on 12Aug20
- GSM7716386 PBMC of CS3392 on 17Jul20
- GSM7716387 PBMC of CS3392 on 27Jul20
- GSM7716388 PBMC of CS3392 on 3Aug20
- GSM7716389 PBMC of CS3392 on 6Dec21
- GSM7716390 PBMC of CY0001 on 8Sep20
- GSM7716391 Lymph node of CS3392
- GSM7716392 Sorted CD45- CD31+ of CS3392
- GSM7716393 Sorted CD45- CD31- of CS3392
- GSE241097 Multicentric Castleman Disease 13 samples shares multicentric, castleman
- GSE256089 scRNA-seq analyses of HTO-tagged human peripheral blood mononuclear cells collected at the ART timepoint during HIV-1 disease 32 samples shares collected
- GSE263321 Castleman disease human lymph node tissue 24 samples shares castleman
- GSE225066 Transcriptomic profiling performed in bladder carcinomas collected from Neodurvarib clinical trial (NCT03534492) 26 samples shares collected
- GSE144216 Robust RNA-Seq of aRNA-amplified single cell material collected by patch clamp 73 samples shares collected
- GSE333160 Delayed processing of CPT-collected blood preserves transcriptomic and genomic features of propagated circulating tumor cells 9 samples shares collected
- GSE290387 RNA-sequencing from nasal curettes or swabs collected from young children aged 1-5 60 samples shares collected
- GSE240306 High Rates of Placental Inflammation in Samples Collected by the MOMI Consortium 56 samples shares collected
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.