Transcriptome-based network analysis reveals a spectrum model of human macrophage activation
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 412 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Samples
- 412 samples: 412 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 expression table (series matrix) and the array files, from NCBI.
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 GSE47189_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA205047 and SRA study SRP022971. 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 the first 400 of 412 sample titles: 400 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.
- GSM1140407 B cell [5342595013_G]
- GSM1140408 B cell [5342595013_I]
- GSM1140409 B cell [5342595027_I]
- GSM1140410 DC_reg [5342595013_D]
- GSM1140411 DC_imm [5342595013_E]
- GSM1140412 DC_mat [5342595013_H]
- GSM1140413 DC_mat [5342595013_L]
- GSM1140414 DC_imm [5342595027_A]
- GSM1140415 DC_mat [5342595027_D]
- GSM1140416 DC_reg [5342595027_E]
- GSM1140417 DC_imm [5342595027_H]
- GSM1140418 DC_reg [5342595027_J]
- GSM1140419 DC_imm [5376074046_A]
- GSM1140420 DC_upLPS_10_24h [5376074046_B]
- GSM1140421 DC_upLPS_10_24h [5376074046_C]
- GSM1140422 DC_upLPS_10_24h [5376074046_D]
- GSM1140423 DC_upLPS_10_24h [5376074046_E]
- GSM1140424 DC_imm [5376074046_F]
- GSM1140425 DC_imm [5376074046_G]
- GSM1140426 DC_upLPS_10_24h [5376074046_H]
- GSM1140427 DC_imm [5376074046_I]
- GSM1140428 DC_imm [5376074046_J]
- GSM1140429 DC_imm [5376074046_K]
- GSM1140430 DC_upLPS_10_24h [5376074046_L]
- GSM1140431 DC_imm [5376074048_A]
- GSM1140432 DC_imm [5376074048_B]
- GSM1140433 DC_upLPS_10_24h [5376074048_C]
- GSM1140434 DC_imm [5376074048_D]
- GSM1140435 DC_imm [5376074048_E]
- GSM1140436 DC_imm [5376074048_F]
- GSM1140437 DC_upLPS_10_24h [5376074048_G]
- GSM1140438 DC_upLPS_10_24h [5376074048_H]
- GSM1140439 DC_upLPS_10_24h [5376074048_I]
- GSM1140440 DC_upLPS_10_24h [5376074048_J]
- GSM1140441 DC_imm [5376074048_K]
- GSM1140442 DC_upLPS_10_24h [5376074048_L]
- GSM1140443 M0_GMCSF_72h [4487653414_E]
- GSM1140444 M_GMCSF_IL4_72h [4487653415_E]
- GSM1140445 M_GMCSF_TPP_72h [4487653415_G]
- GSM1140446 M_GMCSF_IFNg_72h [4487653415_H]
+ 372 more — browse all 412 samples with per-sample file links →
- GSE253006 Differential effects of tofacitinib on macrophage activation contribute to lack of response in ulcerative colitis patients 23 samples shares macrophage, activation
- GSE320020 Macrophage–Fibroblast Signaling Network Identified by Single-Cell RNA Sequencing in Juvenile Systemic Sclerosis 11 samples shares macrophage, network
- GSE273700 Whole transcriptome analysis reveals T cell signaling activation in septic patients with thrombocytopenia 104 samples shares activation
- GSE327289 Cerebrovascular Single-Nucleus RNA-Seq Reveals Heat Shock Activation and Vascular Remodeling in Alzheimer’s Disease and Primary Tauopathies 76 samples shares activation
- GSE292059 Inflammatory Epithelial and Macrophage Pathways Underlie Residual Asthma Exacerbations in Urban Children Treated with Mepolizumab 965 samples shares macrophage
- GSE310252 Transcriptome-based classification of resected pancreatic ductal adenocarcinoma enhances prognostic modelling accuracy of overall survival following adjuvant treatment 118 samples shares transcriptome-based
- GSE240497 Activation of a nongenetic AHR-ELMSAN1 axis optimizes BET-targeting therapy and suppresses leukemia stem cells in preclinical models 66 samples shares activation
- GSE282668 TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration 54 samples shares activation
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.