Transcriptomic analysis of monocytes stimulated with M-CSF in the presence or absence of PFM037 or TNF or TNF +PFM037
RNA-seq (gene expression) · mouse · 16 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
- Mus musculus (mouse)
- Samples
- 16 samples: 16 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.
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 GSE155132_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: 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 PRJNA648761 and SRA study SRP273630. 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 16 sample titles: 16 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.
- GSM4695947 WT1_control [1]
- GSM4695948 WT3_PFM037 [10]
- GSM4695949 WT3_TNF [11]
- GSM4695950 WT3_PFM037_TNF [12]
- GSM4695951 WT4_control [13]
- GSM4695952 WT4_PFM037 [14]
- GSM4695953 WT4_TNF [15]
- GSM4695954 WT4_PFM037_TNF [16]
- GSM4695955 WT1_PFM037 [2]
- GSM4695956 WT1_TNF [3]
- GSM4695957 WT1_PFM037_TNF [4]
- GSM4695958 WT2_control [5]
- GSM4695959 WT2_PFM037 [6]
- GSM4695960 WT2_TNF [7]
- GSM4695961 WT2_PFM037_TNF [8]
- GSM4695962 WT3_control [9]
- GSE239946 Signatures of IL1b, IL6 and TNFa in immune cell-types 209 samples shares tnf
- GSE285241 Transcriptomic profiles of the maternal-fetal interface in wild-type and C1qtnf6-KO mice 24 samples shares tnf
- GSE232746 The GPR84 molecule is a mediator of a subpopulation of retinal microglia that promote TNF/IL-1α expression via the rho-ROCK pathway after optic nerve injury II 144 samples shares tnf
- GSE318351 IL1A enhances TNF-induced retinal ganglion cell death 109 samples shares tnf
- GSE294628 Transcriptomic analysis of epidermal sheets 1 week after induced keratinocyte deletion of A20 (Tnfaip3) in adult mice 8 samples shares tnf
- GSE304254 STING induces ZBP1-mediated necroptosis independently of TNFR1 and FADD 53 samples shares tnf
- GSE304646 Cytokine–ontogeny interaction shapes macrophage transcriptional states (combined GM-CSF– and M-CSF–derived macrophages) 47 samples shares m-csf
- GSE312134 Gene expression profiles of GM-CSF cultured bone marrow cells treated with HCQ or cGAMP. 42 samples shares m-csf
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.