CRISPR activation screens identify the SWI-SNF ATPases as suppressors of ferroptosis
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 65 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)
- Samples
- 65 samples: 65 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
- CRISPR activation screens identify the SWI/SNF ATPases as suppressors of ferroptosisCell reports · 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 GSE245249_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 PRJNA1027452 and SRA study SRP466029. 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 65 sample titles: 65 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.
- GSM7839336 SAM24399619_BRM_Dox_Rep1
- GSM7839337 SAM24399625_BRM_Dox_Rep2
- GSM7839338 SAM24399616_BRM_NoDox_Rep1
- GSM7839339 SAM24399622_BRM_NoDox_Rep2
- GSM7839340 SAM24410226_siNT_Rep1
- GSM7839341 SAM24410227_siNT_Rep2
- GSM7839342 SAM24410228_siBRM_Rep1
- GSM7839343 SAM24410229_siBRM_Rep2
- GSM7839344 SAM24403640_WT_Rep1
- GSM7839345 SAM24403643 _WT_Rep2
- GSM7839346 SAM24403642_LACZ_Rep1
- GSM7839347 SAM24403645_LACZ_Rep2
- GSM7839348 SAM24403641 _KR_Rep1
- GSM7839349 SAM24403644 _KR_Rep2
- GSM7839350 SAM24403646 _TM_Rep1
- GSM7839351 SAM24403647 _TM_Rep2
- GSM7839352 SAM24401733_WT_Rep1
- GSM7839353 SAM24401734_WT_Rep2
- GSM7839354 SAM24401735_WT_Rep3
- GSM7839355 SAM24401736_TM_Rep1
- GSM7839356 SAM24401737_TM_Rep2
- GSM7839357 SAM24401738_TM_Rep3
- GSM7839358 SAM24401739_KR_Rep1
- GSM7839359 SAM24401740_KR_Rep2
- GSM7839360 SAM24401741_KR_Rep3
- GSM7839361 SAM24401742_LACZ_Rep1
- GSM7839362 SAM24401743_LACZ_Rep2
- GSM7839363 SAM24401744_LACZ_Rep3
- GSM7839368 SAM24402081_scRNA-seq_BRM_nodox
- GSM7839369 SAM24402082_scRNA-seq_BRM_dox
- GSM7839370 SAM24402086_BRM_nodox
- GSM7839371 SAM24402087_BRM_dox
- GSM7839372 SAM24402063_BRM_nodox
- GSM7839373 SAM24402064_BRM_dox
- GSM7839374 SAM24403189_BRM_nodox_rep1
- GSM7839375 SAM24403190_BRM_nodox_rep2
- GSM7839376 SAM24403191_BRM_dox_rep1
- GSM7839377 SAM24403192_BRM_dox_rep2
- GSM7839378 SAM24403193_BRM_nodox_ML210_rep1
- GSM7839379 SAM24403194_BRM_nodox_ML210_rep2
+ 25 more — browse all 65 samples with per-sample file links →
- GSE245239 CRISPR activation screens identify the SWI-SNF ATPases as suppressors of ferroptosis [NGS3752_RNA] 12 samples shares swi-snf, crispr, suppressors, ferroptosis, activation, screens, atpases
- GSE288996 Simultaneous single cell CRISPR, RNA, and ATAC-seq enables multiomic CRISPR screens to identify gene regulatory relationships 15 samples shares crispr, screens
- GSE308629 Pooled CRISPR screens identify genes and non-coding genomic regions that regulate red blood cell density 99 samples shares crispr, screens
- GSE243457 Identifying human pre-mRNA cleavage and polyadenylation factors by genome-wide CRISPR screens in a dual fluorescence readthrough reporter 28 samples shares crispr, screens
- GSE305958 CRISPR Screens Identify the ATPase VCP as a Druggable Therapeutic Vulnerability in Cholangiocarcinoma 14 samples shares crispr, screens
- GSE224986 Single-cell CRISPRi screens of breast cancer associated enhancers 94 samples shares crispr, screens
- GSE271444 A CRISPR-Activation CROP-seq Screen Identifies HMGN1 as a Dosage Sensitive Regulator of Heart Defects in Down Syndrome (scRNA-Seq) 49 samples shares crispr, activation
- GSE278910 Pooled CRISPR screens with joint single-nucleus chromatin accessibility and transcriptome profiling [CUT&RUN] 30 samples shares crispr, screens
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.