ASCL1-ChiP sequence data of small cell lung cancer cell lines
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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
- 10 samples: 2 × H1836, ASCL1, ChIP, vs 2 × H1836, IgG1, ChIP, vs 2 × SHP77, ASCL1, ChIP, vs 2 × SHP77, IgG1, ChIP,Groups 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
- FOXA2 promotes metastatic competence in small cell lung cancerNature communications · 2025
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 GSE281524_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 PRJNA1184328 and SRA study SRP544317. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 8 samples.
How we read this: 4 replicated groups read from 10 sample titles; they account for 8 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.
- GSM8622658 H1836, ASCL1, ChIP, rep1 H1836, ASCL1, ChIP,
- GSM8622659 H1836, ASCL1, ChIP, rep2 H1836, ASCL1, ChIP,
- GSM8622660 H1836, IgG1, ChIP, rep1 H1836, IgG1, ChIP,
- GSM8622661 H1836, IgG1, ChIP, rep2 H1836, IgG1, ChIP,
- GSM8622662 H1836, Input
- GSM8622663 SHP77, ASCL1, ChIP, rep1 SHP77, ASCL1, ChIP,
- GSM8622664 SHP77, ASCL1, ChIP, rep2 SHP77, ASCL1, ChIP,
- GSM8622665 SHP77, IgG1, ChIP, rep1 SHP77, IgG1, ChIP,
- GSM8622666 SHP77, IgG1, ChIP, rep2 SHP77, IgG1, ChIP,
- GSM8622667 SHP77, input
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- GSE223503 Non-small Cell Lung Cancer Brain Metastasis Atlas 136 samples shares small, lung
- GSE274975 RNA-sequencing of non-small cell lung cancer tissue samples 61 samples shares small, lung
- GSE223499 Non-small Cell Lung Cancer Brain Metastasis Atlas [single nuclei RNAseq] 42 samples shares small, lung
- GSE303152 Neuronal-Activity Dependent Mechanisms of Small Cell Lung Cancer Pathogenesis 36 samples shares small, lung
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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.