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ZC3H13 and WTAP KO in hMDMs multi stimuli(NGS5421)

GSE268352 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/08/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 48 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
Systematic perturbation screens identify regulators of inflammatory macrophage states and a role for TNF mRNA m6A modificationNature genetics · 2024
Summary (written by the submitters)
Here, we revealed an immunosuppressive role of m6A mediated by ZC3H13 and WTAP on TNF-driven inflammatory phenotype in human macrophages. In the following experiment we would like to investigate if the negative regulatory role of m6A is consistent across multiple stimuli using innate ligands (LPS, R848 and polyIC). We generated ZC3H13 KOs, WTAP KOs and NTC (WT) in monocyte-derived macrophages from 4 individual human donors and stimulated cells over night with LPS (5ng/ml) , R848 (50ng/ml) , polyIC (50ng/ml) and unstimulated cells as control. This yielded a total of 48 total samples.
Published in
Systematic perturbation screens identify regulators of inflammatory macrophage states and a role for TNF mRNA m6A modification
Haag SM, Xie S, Eidenschenk C et al. · Nature genetics 2024 · PMID 39443811 · doi:10.1038/s41588-024-01962-w
This dataset
Open GSE268352 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 GSE268352_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 PRJNA1116552 and SRA study SRP509888. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39443811) ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.