Mapping the Cellular Biogeography of Human Bone Marrow Niches Using Single-Cell Transcriptomics
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
- Mapping the cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imagingCell · 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 GSE253355_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 PRJNA1065394 and SRA study SRP483982. 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.
- GSM8019212 H14_MACS_scRNA-seq
- GSM8019213 H21_scRNA-seq
- GSM8019214 H23_scRNA-seq
- GSM8019215 H24_scRNA-seq
- GSM8019216 H32_scRNA-seq
- GSM8019217 H33_scRNA-seq
- GSM8019218 H34_scRNA-seq
- GSM8019219 H35_scRNA-seq
- GSM8019220 H36_scRNA-seq
- GSM8019221 H38_scRNA-seq
- GSM8019222 H39_scRNA-seq
- GSM8019223 H41_scRNA-seq
- GSE271107 Single-cell RNA sequencing of bone marrow aspirate samples from multiple myeloma and its precursor conditions 19 samples shares single-cell, marrow, bone
- GSE278688 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC [scRNA-Seq] 29 samples shares single-cell, cellular
- GSE326201 Single-cell RNA sequencing of human hepatocellular carcinoma and adjacent non-tumour liver tissues reveals etiology-associated and etiology-independent tumour microenvironmental features 18 samples shares single-cell, cellular
- GSE299340 Single-cell RNA sequencing reveals B cell-related immunosuppressive landscape and a potential suppressor in hepatocellular carcinoma 10 samples shares single-cell, cellular
- GSE278694 Integrated Single-Cell and Spatial Transcriptomics Uncover Distinct Cellular Subtypes Involved in Neural Invasion in PDAC 88 samples shares single-cell, cellular
- GSE334503 Mapping immune cellular landscapes and vaccine responses across a spectrum of health and immunodeficiency [CITE-seq] 10 samples shares cellular, mapping
- GSE305971 Integrative single-cell analysis reveals malignant archetypes and proliferative hierarchies in multiple myeloma 2105 samples shares single-cell
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares single-cell
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.