Tumor-associated Schwann cell remodeling under metabolic stress via lactate sensing orchestrates [ChIP-seq, MeRIP-seq, RNA-seq]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 36 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)
- Topic
- Pancreatic cancerThis series is part of our curated briefing on it.
- Samples
- 36 samples: 36 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.
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 GSE303766_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 PRJNA1297650 and SRA study SRP603954. 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 36 sample titles: 36 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.
- GSM9135541 NDPC SC-1, replicate 1, MeRIP-seq
- GSM9135542 NDPC SC-2, replicate 2, MeRIP-seq
- GSM9135543 DPC SC-1, replicate 1, MeRIP-seq
- GSM9135544 DPC SC-2, replicate 2, MeRIP-seq
- GSM9135545 sgM16-1, replicate 1, MeRIP-seq
- GSM9135546 sgM16-2, replicate 2, MeRIP-seq
- GSM9135547 sgNC-1, replicate 1, MeRIP-seq
- GSM9135548 sgNC-2, replicate 2, MeRIP-seq
- GSM9135549 NDPC SC-1, replicate 1, MeRIP-seq input
- GSM9135550 NDPC SC-2, replicate 2, MeRIP-seq input
- GSM9135551 DPC SC-1, replicate 1, MeRIP-seq input
- GSM9135552 DPC SC-2, replicate 2, MeRIP-seq input
- GSM9135553 sgM16-1, replicate 1, MeRIP-seq input
- GSM9135554 sgM16-2, replicate 2, MeRIP-seq input
- GSM9135555 sgNC-1, replicate 1, MeRIP-seq input
- GSM9135556 sgNC-2, replicate 2, MeRIP-seq input
- GSM9135557 NDPC SC-1, replicate 1, RNA-seq
- GSM9135558 NDPC SC-2, replicate 2, RNA-seq
- GSM9135559 DPC SC-1, replicate 1, RNA-seq
- GSM9135560 DPC SC-2, replicate 2, RNA-seq
- GSM9135561 sgM16-1, replicate 1, RNA-seq
- GSM9135562 sgM16-2, replicate 2, RNA-seq
- GSM9135563 sgNC-1, replicate 1, RNA-seq
- GSM9135564 sgNC-2, replicate 2, RNA-seq
- GSM9135565 SC shNC-1, replicate 1, ChIP-seq
- GSM9135566 SC shNC-2, replicate 1, ChIP-seq
- GSM9135567 SC shCTCF-1, replicate 1, ChIP-seq
- GSM9135568 SC shCTCF-2, replicate 1, ChIP-seq
- GSM9135569 SC shNC-1, replicate 1, ChIP-seq input
- GSM9135570 SC shNC-2, replicate 1, ChIP-seq input
- GSM9135571 SC shCTCF-1, replicate 1, ChIP-seq input
- GSM9135572 SC shCTCF-2, replicate 1, ChIP-seq input
- GSM9135573 SC shNC-1, replicate 1, RNA-seq
- GSM9135574 SC shNC-2, replicate 1, RNA-seq
- GSM9135575 SC shCTCF-1, replicate 1, RNA-seq
- GSM9135576 SC shCTCF-2, replicate 1, RNA-seq
- GSE143804 MYC ChIP-seq in human pancreatic ductal adenocarcinoma cells 6 samples same disease briefing · shares chip-seq
- GSE268524 A robust circulating microRNA signature for diagnosis and early detection in pancreatobiliary cancer 1403 samples same disease briefing
- GSE143584 Gene expression from laser capture microdissected epithelium and stroma during pancreatic carcinogenesis 366 samples same disease briefing
- GSE71729 Virtual Microdissection of Pancreatic Ductal Adenocarcinoma Reveals Tumor and Stroma Subtypes. 357 samples same disease briefing
- GSE113616 Stromal Fibroblasts Drive Single Cell Heterogeneity in Pancreatic Cancer 189 samples same disease briefing
- GSE134236 Mutant Kras co-opts a progenitor-derived enhancer network to initiate pancreatic tumorigenesis 166 samples same disease briefing
- GSE81314 Shotgun sequencing of 5-hydroxymethylcysotine circulating cell-free DNA from the blood distinguishes solid tumor tissues of origin 126 samples same disease briefing
- GSE273490 Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [CUT&Run] 120 samples same disease briefing
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.