RNA-Seq of VUMC-DIPG10 and HSJD-DIPG007 human diffuse intrinsic pontine glioma cells treated with a copper chelator
RNA-seq (gene expression) · human · 12 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 12 samples: 3 × DIPG010_CTRL vs 3 × DIPG010_TEPA vs 3 × DIPG007_CON vs 3 × DIPG007_TEPAGroups 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 GSE215220_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA889380 and SRA study SRP401959. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.
- GSM6628137 DIPG010_CTRL_rep1 DIPG010_CTRL
- GSM6628138 DIPG010_CTRL_rep2 DIPG010_CTRL
- GSM6628139 DIPG010_CTRL_rep3 DIPG010_CTRL
- GSM6628140 DIPG010_TEPA_rep1 DIPG010_TEPA
- GSM6628141 DIPG010_TEPA_rep2 DIPG010_TEPA
- GSM6628142 DIPG010_TEPA_rep3 DIPG010_TEPA
- GSM6628143 DIPG007_CON_rep1 DIPG007_CON
- GSM6628144 DIPG007_CON_rep2 DIPG007_CON
- GSM6628145 DIPG007_CON_rep3 DIPG007_CON
- GSM6628146 DIPG007_TEPA_rep1 DIPG007_TEPA
- GSM6628147 DIPG007_TEPA_rep2 DIPG007_TEPA
- GSM6628148 DIPG007_TEPA_rep3 DIPG007_TEPA
- GSE250466 Oncohistone H3.3K27M-driven CREB5/ID1 Axis Mediates the Malignant Cell States of Diffuse Intrinsic Pontine Glioma (DIPG) [RNA-seq] 10 samples shares intrinsic, rna-seq, diffuse, pontine
- GSE288070 Radiotherapy plus neoadjuvant and concomitant IL-13Rα2-directed immunotoxin therapy for diffuse intrinsic pontine glioma 19 samples shares intrinsic, diffuse, pontine
- GSE185760 RNA-Seq of MDA-MB-231 human triple-negative breast cancer cells treated with a copper chelator 9 samples shares chelator, rna-seq, treated
- GSE50025 Diffuse Intrinsic Pontine Glioma 145 samples shares intrinsic, diffuse, pontine
- GSE50024 Affymetrix SNP 6.0 array data for Diffuse Intrinsic Pontine Glioma 72 samples shares intrinsic, diffuse, pontine
- GSE50022 Illumina Infinium 450K array data for Diffuse Intrinsic Pontine Glioma 28 samples shares intrinsic, diffuse, pontine
- GSE250464 Oncohistone H3.3K27M-driven CREB5/ID1 Axis Mediates the Malignant Cell States of Diffuse Intrinsic Pontine Glioma (DIPG) [CUT&Tag] 26 samples shares intrinsic, diffuse, pontine
- GSE225029 SUV39H1 inhibition by Chaetocin targets stemness and oncogenic networks and synergizes with ONC201 against Diffuse intrinsic pontine gliomas 12 samples shares intrinsic, diffuse, pontine
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.