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Complexity of synovial fluid-derived monocyte–macrophage lineage cells in knee osteoarthritis

GSE279915 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/10/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
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.
Summary (written by the submitters)
Synovial fluid (SF)-derived monocyte–macrophage lineage (MON–Mϕ) cells in knee osteoarthritis (KOA) remain poorly understood. This lineage consists of four subpopulations with considerable interindividual variability that correlates with the distribution and activation of other immune cells. The most abundant subpopulation was that of CD11b+CD14−CD16− myeloid dendritic cells (mDCs; type cDC2), which were inactive and exhibited low cytokine production, low T-lymphocyte stimulation, high migratory ability comparing to other MON–Mϕ cells.
Read the full summary ↓
Other major subpopulations included CD11b+CD14+CD16− monocyte-like cells and CD11b+CD14+CD16+ macrophages. A subpopulation of CD11b−CD14−CD16− mDCs (type cDC1) was less common. To confirm the identity of MON–Mϕ subpopulations characterised through flow cytometry, we performed bulk RNA-seq analysis on sorted CD11b+CD14−CD16−, CD11b+CD14+CD16− and CD11b+CD14+CD16+ MON–Mϕ subpopulations from the SF of four patients with KOA with a predominance of MON–Mϕ lineage cells. The CD11b+CD14+CD16− and CD11b+CD14+CD16+ cells shared a similar transcriptomic profile. However, CD11b+CD14−CD16− cells were remarkably distinct from other CD11b+ populations. The dataset is part of a study published by Mikulkova et al. Cell Reports.
This dataset
Open GSE279915 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE279915_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1175382 and SRA study SRP539688. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 samples, each with a distinct title — no replicated groups

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.

Samples in this study
Datasets on a similar topic

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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.