Decoding the immune checkpoint signatures in human atherosclerosis: implications of type 2 diabetes and lipid-lowering intervention [human PBMC scRNA-Seq]
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: 12 × PBMC_scRNAseq_NT vs 12 × PBMC_scRNAseq_LLGroups 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
- Immune checkpoint landscape of human atherosclerosis and influence of cardiometabolic factorsNature cardiovascular research · 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 GSE272294_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 PRJNA1136035 and SRA study SRP520022. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 24 samples.
How we read this: 2 replicated groups read from 24 sample titles; they account for 24 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.
- GSM8397940 PBMC_scRNAseq_NT_1 PBMC_scRNAseq_NT
- GSM8397941 PBMC_scRNAseq_LL_1 PBMC_scRNAseq_LL
- GSM8397942 PBMC_scRNAseq_NT_2 PBMC_scRNAseq_NT
- GSM8397943 PBMC_scRNAseq_LL_2 PBMC_scRNAseq_LL
- GSM8397944 PBMC_scRNAseq_NT_3 PBMC_scRNAseq_NT
- GSM8397945 PBMC_scRNAseq_LL_3 PBMC_scRNAseq_LL
- GSM8397946 PBMC_scRNAseq_NT_4 PBMC_scRNAseq_NT
- GSM8397947 PBMC_scRNAseq_LL_4 PBMC_scRNAseq_LL
- GSM8397948 PBMC_scRNAseq_NT_5 PBMC_scRNAseq_NT
- GSM8397949 PBMC_scRNAseq_LL_5 PBMC_scRNAseq_LL
- GSM8397950 PBMC_scRNAseq_NT_6 PBMC_scRNAseq_NT
- GSM8397951 PBMC_scRNAseq_LL_6 PBMC_scRNAseq_LL
- GSM8397952 PBMC_scRNAseq_NT_7 PBMC_scRNAseq_NT
- GSM8397953 PBMC_scRNAseq_LL_7 PBMC_scRNAseq_LL
- GSM8397954 PBMC_scRNAseq_NT_8 PBMC_scRNAseq_NT
- GSM8397955 PBMC_scRNAseq_LL_8 PBMC_scRNAseq_LL
- GSM8397956 PBMC_scRNAseq_NT_9 PBMC_scRNAseq_NT
- GSM8397957 PBMC_scRNAseq_LL_9 PBMC_scRNAseq_LL
- GSM8397958 PBMC_scRNAseq_NT_10 PBMC_scRNAseq_NT
- GSM8397959 PBMC_scRNAseq_LL_10 PBMC_scRNAseq_LL
- GSM8397960 PBMC_scRNAseq_NT_11 PBMC_scRNAseq_NT
- GSM8397961 PBMC_scRNAseq_LL_11 PBMC_scRNAseq_LL
- GSM8397962 PBMC_scRNAseq_NT_12 PBMC_scRNAseq_NT
- GSM8397963 PBMC_scRNAseq_LL_12 PBMC_scRNAseq_LL
- GSE246315 Decoding the immune checkpoint signatures in human atherosclerosis: implications of type 2 diabetes and lipid-lowering intervention [human_carotid_plaque] 12 samples shares atherosclerosis, lipid-lowering, implications, intervention, checkpoint, signatures
- GSE267023 scRNA-seq analysis of PBMCs from ischemic stroke patients 16 samples shares pbmc, scrna-seq
- GSE277117 scRNA-seq and genomic reference of PBMC upon TNF Inhibitor Response in Ankylosing Spondylitis 62 samples shares pbmc, scrna-seq
- GSE287043 Unique Mycobacterium tuberculosis-specific blood immune signatures in sarcoidosis: implications for clinical diagnosis 542 samples shares implications, signatures
- GSE242912 MRI and gene signatures in facioscapulohumeral dystrophy muscle: implications for clinical trial design and mechanisms of disease progression 64 samples shares implications, signatures
- GSE253903 High-Dimensional Single-Cell Multimodal Landscape of Human Carotid Atherosclerosis [scRNA-seq] 12 samples shares atherosclerosis, scrna-seq
- GSE335789 scRNA-seq of biophysically separated immune cells in atherosclerosis 8 samples shares atherosclerosis, scrna-seq
- GSE319710 Monocytes defined by platelet interactions and oxidative stress signaling underlie HIV-associated atherosclerosis [scRNA-seq] 48 samples shares atherosclerosis, scrna-seq
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.