Suppressing Aberrant Hedgehog Pathway and Overcoming Resistance to Smoothened Antagonists via Targeting Super-enhancer-driven Transcriptional Dependencies [ChIP-seq]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 14 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
- 14 samples: 14 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
- Targeting Super-Enhancer-Driven Transcriptional Dependencies Suppresses Aberrant Hedgehog Pathway Activation and Overcomes Smoothened Inhibitor ResistanceCancer research · 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 GSE266386_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 PRJNA1106888 and SRA study SRP505250. 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 14 sample titles: 14 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.
- GSM8246091 SmoWT-1, H3K27ac, ChIP
- GSM8246092 SmoWT-1, Input
- GSM8246093 SmoWT-2, H3K27ac, ChIP
- GSM8246094 SmoWT-2, Input
- GSM8246095 SMB56-1, H3K27ac, ChIP
- GSM8246096 SMB56-1, Input
- GSM8246097 SMB56-2, H3K27ac, ChIP
- GSM8246098 SMB56-2, Input
- GSM8246099 SmoWT-MB-GLI2-deltaN, HA-tag, ChIP
- GSM8246100 SmoWT-MB-GLI2-deltaN, Input
- GSM8246101 SHH-MB_PDX1, H3K27ac, ChIP
- GSM8246102 SHH-MB_PDX1, Input
- GSM8246103 SHH-MB_PDX2, H3K27ac, ChIP
- GSM8246104 SHH-MB_PDX2, Input
- GSE267542 Tumor intrinsic METTL5 induces immune resistance in ovarian cancer by suppressing ferroptosis 18 samples shares suppressing, resistance
- GSE283532 MOZ and HBO1 Histone Acetyltransferase Complexes Are Molecular Dependencies and Therapeutic Targets in NUP98-Rearranged Acute Myeloid Leukemia 70 samples shares dependencies
- GSE296402 Interleukin-23 promotes a pro-inflammatory Th17 cell state by stabilizing RORγt and suppressing glucocorticoid receptor activity 66 samples shares suppressing
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.