Altered DNA methylation underlies monocyte dysregulation and immune exhaustion memory in sepsis [CUT&RUN]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
- 18 samples: 6 conditions, mostly in triplicateGroups 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
- Altered DNA methylation underlies monocyte dysregulation and immune exhaustion memory in sepsisCell reports · 2024
Read the full summary ↓
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 GSE253201_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 PRJNA1064414 and SRA study SRP483555. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 18 samples.
How we read this: 6 replicated groups read from 18 sample titles; they account for 18 of them. 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.
- GSM8016296 BMMC, PBS, H3K4me1, rep1 BMMC, PBS, H3K4me1,
- GSM8016297 BMMC, PBS, H3K4me3, rep1 BMMC, PBS, H3K4me3,
- GSM8016298 BMMC, PBS, IgG Control, rep1 BMMC, PBS, IgG Control,
- GSM8016299 BMMC, LPS, H3K4me1, rep1 BMMC, LPS, H3K4me1,
- GSM8016300 BMMC, LPS, H3K4me3, rep1 BMMC, LPS, H3K4me3,
- GSM8016301 BMMC, LPS, IgG Control, rep1 BMMC, LPS, IgG Control,
- GSM8016302 BMMC, PBS, H3K4me1, rep2 BMMC, PBS, H3K4me1,
- GSM8016303 BMMC, PBS, H3K4me3, rep2 BMMC, PBS, H3K4me3,
- GSM8016304 BMMC, PBS, IgG Control, rep2 BMMC, PBS, IgG Control,
- GSM8016305 BMMC, LPS, H3K4me1, rep2 BMMC, LPS, H3K4me1,
- GSM8016306 BMMC, LPS, H3K4me3, rep2 BMMC, LPS, H3K4me3,
- GSM8016307 BMMC, LPS, IgG Control, rep2 BMMC, LPS, IgG Control,
- GSM8016308 BMMC, PBS, H3K4me1, rep3 BMMC, PBS, H3K4me1,
- GSM8016309 BMMC, PBS, H3K4me3, rep3 BMMC, PBS, H3K4me3,
- GSM8016310 BMMC, PBS, IgG Control, rep3 BMMC, PBS, IgG Control,
- GSM8016311 BMMC, LPS, H3K4me1, rep3 BMMC, LPS, H3K4me1,
- GSM8016312 BMMC, LPS, H3K4me3, rep3 BMMC, LPS, H3K4me3,
- GSM8016313 BMMC, LPS, IgG Control, rep3 BMMC, LPS, IgG Control,
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- GSE303384 Mechanism of maintenance and establishment of repression by the Mtg16 tumor suppressor [CUT&RUN, ChIP-Seq] 92 samples shares cut, run
- GSE306261 Astrocyte glucocorticoid receptor signaling restricts neuronal plasticity [CUT&RUN] 50 samples shares cut, run
- GSE298002 Stage-specific Epigenetic Priming Amplifies Gene Activation During Lineage Commitment [CUT&Run] 38 samples shares cut, run
- GSE274875 A mutant ASXL1-EHMT complex contributes to heterochromatin dysfunction in clonal hematopoiesis and chronic monomyelocytic leukemia [Cut & Run] 38 samples shares cut, run
- GSE293129 Enhancer rewiring orchestrates inflammation and loss of cell identity during muscle stem cell aging [CUT&RUN] 36 samples shares cut, run
- GSE225202 REV-ERBα regulates regulatory T cell function in inflammatory bowel disease [CUT&RUN] 29 samples shares cut, run
- GSE326112 Interleukin-12 drives a rapid STAT4/DDX5-dependent change in the RNA polymerase II landscape for IFN-γ production by NK cells [CUT&RUN] 18 samples shares cut, run
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.