The post-septic peripheral myeloid compartment reveals unexpected diversity in myeloid-derived suppressor cells
Single-cell RNA-seq · human · 34 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 34 samples: 34 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
- The post-septic peripheral myeloid compartment reveals unexpected diversity in myeloid-derived suppressor cellsFrontiers in immunology · 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 GSE252331_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 PRJNA1060229 and SRA study SRP481033. 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 34 sample titles: 34 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.
- GSM7999550 Sepsis 5, CCI, Day 14, GEX
- GSM7999551 Sepsis 6, RAP, Day 14, GEX
- GSM7999552 Sepsis 7, CCI, Day 14, GEX
- GSM7999553 Sepsis 8, RAP, Day 14, GEX
- GSM7999554 Sepsis 9, RAP, Day 14, GEX
- GSM7999555 Sepsis 10, Day 4, GEX
- GSM7999556 Sepsis 11, Day 4, GEX
- GSM7999557 Sepsis 12, RAP, Day 14, GEX
- GSM7999558 Sepsis 13, Day 4, GEX
- GSM7999559 Sepsis 14, Day 4, GEX
- GSM7999560 Healthy Control 6, GEX
- GSM7999561 Healthy Control 7, GEX
- GSM7999562 Healthy Control 8, GEX
- GSM7999563 Healthy Control 9, GEX
- GSM7999564 Healthy Control 10, GEX
- GSM7999565 Healthy Control 11, GEX
- GSM7999566 Healthy Control 12, GEX
- GSM7999567 Sepsis 5, CCI, Day 14, ADT
- GSM7999568 Sepsis 6, RAP, Day 14, ADT
- GSM7999569 Sepsis 7, CCI, Day 14, ADT
- GSM7999570 Sepsis 8, RAP, Day 14, ADT
- GSM7999571 Sepsis 9, RAP, Day 14, ADT
- GSM7999572 Sepsis 10, Day 4, ADT
- GSM7999573 Sepsis 11, Day 4, ADT
- GSM7999574 Sepsis 12, RAP, Day 14, ADT
- GSM7999575 Sepsis 13, Day 4, ADT
- GSM7999576 Sepsis 14, Day 4, ADT
- GSM7999577 Healthy Control 6, ADT
- GSM7999578 Healthy Control 7, ADT
- GSM7999579 Healthy Control 8, ADT
- GSM7999580 Healthy Control 9, ADT
- GSM7999581 Healthy Control 10, ADT
- GSM7999582 Healthy Control 11, ADT
- GSM7999583 Healthy Control 12, ADT
- GSE287333 Myeloid-derived suppressor cells exhibit distinct characteristics in bone marrow and blood of individuals with diffuse large B-cell lymphoma 19 samples shares myeloid-derived, suppressor, myeloid
- GSE276503 Myeloid-derived IL1B drives epithelial and stromal cell remodeling during chronic rhinosinusitis and nasal polyps [scRNA-seq] 33 samples shares myeloid-derived, myeloid
- GSE281106 Single-cell RNA-seq of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases [scRNAseq_KR_SGI] 352 samples shares peripheral
- GSE255685 Age-related transcriptomic differences in peripheral blood of adolescents with major depressive disorder 279 samples shares peripheral
- GSE243841 Peripheral mRNA expression of first-episode drug-naïve patients with schizophrenia 181 samples shares peripheral
- GSE251778 Sex-specific and multiomic integration enhance accuracy of peripheral blood biomarkers of major depressive disorder [RNA-Seq] 169 samples shares peripheral
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares peripheral
- GSE289582 Baseline tumor features and peripheral blood immune dynamics that underlie efficacy in MSS metastatic colorectal cancer treated with regorafenib, ipilimumab, and nivolumab [Blood] 115 samples shares peripheral
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.