Functionally distinct subset of monocytes in mouse and human blood
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 96 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
- Mus musculus (mouse)
- Samples
- 96 samples: 96 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 GSE148555_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 PRJNA625023 and SRA study SRP256264. 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 96 sample titles: 96 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.
- GSM4473392 Clone1_Plus [ATAC-seq]
- GSM4473393 Clone2_Plus [ATAC-seq]
- GSM4473394 Clone3_Plus [ATAC-seq]
- GSM4473395 Clone4_Plus [ATAC-seq]
- GSM4473396 Clone5_Plus [ATAC-seq]
- GSM4473397 Clone6_Plus [ATAC-seq]
- GSM4473398 Clone7_Plus [ATAC-seq]
- GSM4473399 Clone8_Plus [ATAC-seq]
- GSM4473400 Clone9_Plus [ATAC-seq]
- GSM4473401 Clone10_Plus [ATAC-seq]
- GSM4473402 Clone11_Plus [ATAC-seq]
- GSM4473403 Clone12_Plus [ATAC-seq]
- GSM4473404 Clone13_Plus [ATAC-seq]
- GSM4473405 Clone15_Plus [ATAC-seq]
- GSM4473406 Clone16_Plus [ATAC-seq]
- GSM4473407 Clone17_Plus [ATAC-seq]
- GSM4473408 Clone18_Plus [ATAC-seq]
- GSM4473409 Clone19_Plus [ATAC-seq]
- GSM4473410 Clone20_Plus [ATAC-seq]
- GSM4473411 Clone21_Plus [ATAC-seq]
- GSM4473412 Clone22_Plus [ATAC-seq]
- GSM4473413 Clone23_Plus [ATAC-seq]
- GSM4473414 Clone24_Plus [ATAC-seq]
- GSM4473415 Clone26_Plus [ATAC-seq]
- GSM4473416 Clone1_Minus [ATAC-seq]
- GSM4473417 Clone2_Minus [ATAC-seq]
- GSM4473418 Clone3_Minus [ATAC-seq]
- GSM4473419 Clone4_Minus [ATAC-seq]
- GSM4473420 Clone5_Minus [ATAC-seq]
- GSM4473421 Clone6_Minus [ATAC-seq]
- GSM4473422 Clone7_Minus [ATAC-seq]
- GSM4473423 Clone8_Minus [ATAC-seq]
- GSM4473424 Clone9_Minus [ATAC-seq]
- GSM4473425 Clone10_Minus [ATAC-seq]
- GSM4473426 Clone11_Minus [ATAC-seq]
- GSM4473427 Clone12_Minus [ATAC-seq]
- GSM4473428 Clone13_Minus [ATAC-seq]
- GSM4473429 Clone15_Minus [ATAC-seq]
- GSM4473430 Clone16_Minus [ATAC-seq]
- GSM4473431 Clone17_Minus [ATAC-seq]
+ 56 more — browse all 96 samples with per-sample file links →
- GSE148554 Functionally distinct subset of monocytes in mouse and human blood [RNA-Seq] 48 samples shares functionally, monocytes, distinct, subset, blood
- GSE306514 Chemokine receptor expression patterns delineate distinct interstitial macrophage subsets in the lung and define a trajectory from monocytes to mature macrophages, bulk RNA-sequencing data 24 samples shares monocytes, distinct, subset
- GSE233993 Determining the chromatin accessibility profiles of functionally distinct SHH-medulloblastoma sub-populations 12 samples shares functionally, distinct
- GSE292240 Distinct molecular mechanisms of stress habituation in the mouse hippocampus 266 samples shares distinct
- GSE249734 Antigen experience history directs distinct functional states of CD8+ CAR T cells during the anti-leukemia response 96 samples shares distinct
- GSE341379 Distinct histone 3 lysine methylation states underlie tumor immune surveillance 50 samples shares distinct
- GSE157232 The CD8+ T cell tolerance checkpoint triggers a transcriptionally and epigenetically distinct differentiation state defined by protein translation defects 30 samples shares distinct
- GSE228455 Gene expression profile at single cell level of monocytes sorted from C57BL/6J mouse ear tissue at 3 weeks post Leishmania major infection [scRNA-seq] 218 samples shares monocytes
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.