Identification of the genome-wide binding sites of OCT2 in Reg-1fl/fl- and Reg-1ΔNK-NK cells. [ChIP-Seq]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 12 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
- 12 samples: 12 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
- Deletion of the mRNA endonuclease Regnase-1 promotes NK cell anti-tumor activity via OCT2-dependent transcription of IfngImmunity · 2024
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 GSE237640_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 PRJNA996085 and SRA study SRP450213. 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 12 sample titles: 12 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.
- GSM7635061 WT_Input, rep 1, ChIPseq
- GSM7635062 WT_Input, rep 2, ChIPseq
- GSM7635063 WT_ChIP, rep 1, ChIPseq
- GSM7635064 WT_ChIP, rep 2, ChIPseq
- GSM7635065 KO_Input, rep 1, ChIPseq
- GSM7635066 KO_Input, rep 2, ChIPseq
- GSM7635067 KO_ChIP, rep 1, ChIPseq
- GSM7635068 KO_ChIP, rep 2, ChIPseq
- GSM7635069 WT_Input, rep 3, ChIPseq
- GSM7635070 WT_ChIP, rep 3, ChIPseq
- GSM7635071 KO_Input, rep 3, ChIPseq
- GSM7635072 KO_ChIP, rep 3, ChIPseq
- GSE237639 Transcriptomic profile at single cell level of splenic NK cells from Reg-1fl/fl and Reg-1ΔNK mice [CITE-Seq] 16 samples shares reg-1fl, reg-1
- GSE237642 Transcriptomic profile at single cell level of TIL-NK cells and tumor cells from tumor-bearing Reg-1fl/fl and Reg-1ΔNK mice 4 samples shares reg-1fl, reg-1
- GSE237643 Deletion of the mRNA endonuclease Regnase-1 promotes NK cell anti-tumor activity via OCT2- dependent transcription of Ifng 58 samples shares oct2
- GSE245678 Transcriptomic profile at single cell level of OCT2fl/fl and Ncr(+)/OCT2fl/fl mice [scRNA-seq] 2 samples shares oct2
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.