Application of machine learning (ML) / deep learning (DL) using multiple epigenetic features reveals H3K27Ac as driver of gene expression prediction across patients with glioblastoma
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 11 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
- GlioblastomaThis series is part of our curated briefing on it.
- Samples
- 11 samples: 10 distinct titles, 1 of them repeatedGroups 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.
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 GSE296948_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 PRJNA1261975 and SRA study SRP584749. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 11 sample titles: 10 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.
- GSM8980142 GSC1_Stem_H3K27ac
- GSM8980143 GSC2_Stem_H3K27ac
- GSM8980144 GSC1_Stem_RNApol2
- GSM8980145 GSC2_Stem_RNApol2
- GSM8980146 GSC1_Stem_CTCF
- GSM8980147 GSC2_Stem_CTCF
- GSM8980148 GSC_pooled_input
- GSM8980149 GSC1
- GSM8980150 GSC2
- GSM8980157 GSC1_atac
- GSM8980158 GSC2_atac
- GSE122283 H3K27ac ChIP-seq in GBM cell lines SF763 PTEN-KO and U87 4 samples same disease briefing · shares h3k27ac
- GSE107560 Ivy Glioblastoma Atlas Project 305 samples same disease briefing · shares glioblastoma
- GSE13041 Gene expression analysis of glioblastomas identifies the major molecular basis for the prognostic benefit of younger age 267 samples same disease briefing · shares glioblastoma
- GSE10878 Integrative Genome-wide Analysis of Glioblastoma. 60 samples same disease briefing · shares glioblastoma
- GSE112650 SOX4/11 Enhances NGN2 Reprogramming Glioblastoma Cells into Neuron Cells by Modulating RhoA and CDC42/RAC1 Pathway Activity 30 samples same disease briefing · shares glioblastoma
- GSE112648 SOXC factors as suppressors modulate Rho activity to promote neuronal reprogramming of human glioblastoma cells 18 samples same disease briefing · shares glioblastoma
- GSE112645 SOXC factors as suppressors modulate Rho activity to promote neuronal reprogramming of human glioblastoma cells 12 samples same disease briefing · shares glioblastoma
- GSE115459 Exosome-transmitted RVT1 from reactive astrocytes promotes recurrence glioblastoma proliferation 9 samples same disease briefing · shares glioblastoma
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.