High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis
Single-cell RNA-seq · human · 24 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
- 24 samples: 24 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
- High-Dimensional Single-Cell Multimodal Landscape of Human Carotid AtherosclerosisArteriosclerosis, thrombosis, and vascular biology · 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 GSE253904_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 PRJNA1067637 and SRA study SRP485269. 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 24 sample titles: 24 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.
- GSM8029950 carotid_5, GEX
- GSM8029951 carotid_5, ADT
- GSM8029952 carotid_7, GEX
- GSM8029953 carotid_7, ADT
- GSM8029954 carotid_8, GEX
- GSM8029955 carotid_8, ADT
- GSM8029956 carotid_10, GEX
- GSM8029957 carotid_10, ADT
- GSM8029958 carotid_11, GEX
- GSM8029959 carotid_11, ADT
- GSM8029960 carotid_12, GEX
- GSM8029961 carotid_12, ADT
- GSM8029962 carotid_4, scRNA-seq
- GSM8029963 carotid_6, scRNA-seq
- GSM8029964 carotid_9, scRNA-seq
- GSM8029965 carotid_13, scRNA-seq
- GSM8029966 carotid_14, scRNA-seq
- GSM8029967 carotid_15, scRNA-seq
- GSM8029968 carotid_16, scRNA-seq
- GSM8029969 carotid_17, scRNA-seq
- GSM8029970 carotid_18, scRNA-seq
- GSM8029971 carotid_19, scRNA-seq
- GSM8029972 carotid_20, scRNA-seq
- GSM8029973 carotid_21, scRNA-seq
- GSE327101 Single-Cell Multimodal Atlas Reveals Regulatory Programs in the Human Brain 220 samples shares single-cell, multimodal
- GSE279945 OP3: single-cell multimodal dataset in PBMCs for perturbation prediction benchmarking 102 samples shares single-cell, multimodal
- GSE332630 Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma 22 samples shares single-cell, multimodal
- GSE272005 Genomic and single-cell landscape of transformed cutaneous T-cell lymphoma 32 samples shares single-cell
- GSE253661 Longitudinal single-cell transcriptomics of monocytes, Tfh and gd Tcells following a control human malaria infection. 16 samples shares single-cell
- GSE279392 Single-cell RNA and TCR sequencing from skin, blood and cerebral spinal fluid (CSF) samples from Degos disease patients 116 samples shares single-cell
- GSE196198 Longitudinal single-cell multiomics data for different severity of COVID-19 100 samples shares single-cell
- GSE287976 Single-Cell Omics Analysis of Human Basophils Reveals Two Transcriptionally Distinct Populations 12 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.