METTL3-based epitranscriptomic editing screening identifies functional m6A sites in cancers
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 60 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
- 60 samples: 20 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
- METTL3-based epitranscriptomic editing screening identifies functional m(6)A sites in cancersNature cancer · 2026
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 GSE242447_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 PRJNA1013485 and SRA study SRP458780. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 60 samples.
How we read this: 20 replicated groups read from 60 sample titles; they account for 60 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.
- GSM7763586 22Rv1 cells, shGFP_rep1 22Rv1 cells, shGFP
- GSM7763587 22Rv1 cells, shGFP_rep2 22Rv1 cells, shGFP
- GSM7763588 22Rv1 cells, shGFP_rep3 22Rv1 cells, shGFP
- GSM7763589 22Rv1 cells, shCHD9_1_rep1 22Rv1 cells, shCHD9_1
- GSM7763590 22Rv1 cells, shCHD9_1_rep2 22Rv1 cells, shCHD9_1
- GSM7763591 22Rv1 cells, shCHD9_1_rep3 22Rv1 cells, shCHD9_1
- GSM7763592 22Rv1 cells, shCHD9_2_rep1 22Rv1 cells, shCHD9_2
- GSM7763593 22Rv1 cells, shCHD9_2_rep2 22Rv1 cells, shCHD9_2
- GSM7763594 22Rv1 cells, shCHD9_2_rep3 22Rv1 cells, shCHD9_2
- GSM7763595 22Rv1 cells, T0, rep1 22Rv1 cells, T0,
- GSM7763596 22Rv1 cells, T0, rep2 22Rv1 cells, T0,
- GSM7763597 22Rv1 cells, T0, rep3 22Rv1 cells, T0,
- GSM7763598 22Rv1 cells, T16, rep1 22Rv1 cells, T16,
- GSM7763599 22Rv1 cells, T16, rep2 22Rv1 cells, T16,
- GSM7763600 22Rv1 cells, T16, rep3 22Rv1 cells, T16,
- GSM8080206 ChIP-CHD9, shGFP, rep1 ChIP-CHD9, shGFP,
- GSM8080207 ChIP-CHD9, shGFP, rep2 ChIP-CHD9, shGFP,
- GSM8080208 ChIP-CHD9, shCHD9, rep1 ChIP-CHD9, shCHD9,
- GSM8080209 ChIP-CHD9, shCHD9, rep2 ChIP-CHD9, shCHD9,
- GSM8080210 ChIP-H3K27ac, shGFP, rep1 ChIP-H3K27ac, shGFP,
- GSM8080211 ChIP-H3K27ac, shGFP, rep2 ChIP-H3K27ac, shGFP,
- GSM8080212 ChIP-H3K27ac, shCHD9, rep1 ChIP-H3K27ac, shCHD9,
- GSM8080213 ChIP-H3K27ac, shCHD9, rep2 ChIP-H3K27ac, shCHD9,
- GSM8080218 ATAC-Seq, shGFP, rep1 ATAC-Seq, shGFP,
- GSM8080219 ATAC-Seq, shGFP, rep2 ATAC-Seq, shGFP,
- GSM8080220 ATAC-Seq, shCHD9, rep1 ATAC-Seq, shCHD9,
- GSM8080221 ATAC-Seq, shCHD9, rep2 ATAC-Seq, shCHD9,
- GSM9356503 M3_gNT_rep1 M3_gNT
- GSM9356504 M3_gNT_rep2 M3_gNT
- GSM9356505 M3_gNT_rep3 M3_gNT
- GSM9356506 M3_g1_rep1 M3_g1
- GSM9356507 M3_g1_rep2 M3_g1
- GSM9356508 M3_g1_rep3 M3_g1
- GSM9356509 M3_g2_rep1 M3_g2
- GSM9356510 M3_g2_rep2 M3_g2
- GSM9356511 M3_g2_rep3 M3_g2
- GSM9356523 H358 cells, T0, rep1 lane1 H358 cells, T0, rep1
- GSM9356524 H358 cells, T0, rep2 lane1 H358 cells, T0, rep2
- GSM9356525 H358 cells, T0, rep3 lane1 H358 cells, T0, rep3
- GSM9356526 H358 cells, T16, rep1 lane1 H358 cells, T16, rep1
+ 20 more — browse all 60 samples with per-sample file links →
- GSE276052 CRISPR screening identifies regulators of enhancer mediated androgen receptor transcription in advanced prostate cancer 92 samples shares identifies, screening
- GSE282258 Imaging-based drug screening combined with moleuclar profiling identifies signatures and drivers of therapy resistance in pediatric AML [ATAC-seq] 44 samples shares identifies, screening
- GSE328457 Pooled combinatorial screening identifies transcription factor sets that drive hematopoietic progenitor-like cell fate 39 samples shares identifies, screening
- GSE282423 Imaging-based drug screening combined with moleuclar profiling identifies signatures and drivers of therapy resistance in pediatric AML [RNA-seq] 28 samples shares identifies, screening
- GSE336960 Phenotypic CRISPR screening identifies ZBTB10 as a novel regulator of human trophoblast differentiation 22 samples shares identifies, screening
- GSE310675 CRISPR-Cas9 Screening Identifies Resistance Mechanisms to KRAS Inhibition in Pancreatic Cancer 12 samples shares identifies, screening
- GSE312236 Comprehensive proteogenomic analysis identifies immune targets in microsatellite stable and unstable colorectal cancers 26 samples shares identifies
- GSE254707 Single-cell transcriptomic analysis identifies infiltrating plasmacytoid dendritic cells in psoriasis epidermis 4988 samples shares identifies
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.