Molecular signatures define BAP1-altered meningioma as a distinct CNS tumor with deregulation of Polycomb repressive complex target genes
RNA-seq (gene expression) · human · 29 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
- 29 samples: 13 × BAP1 sample vs 9 × NF2 sample vs 7 × H3K27me3 loss sampleGroups 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
- Molecular signatures define BAP1-altered meningioma as a distinct CNS tumor with deregulation of Polycomb repressive complex target genesNeuro-oncology · 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 GSE287322_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 PRJNA1212133 and SRA study SRP559773. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 29 samples.
How we read this: 3 replicated groups read from 29 sample titles; they account for 29 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.
- GSM8743876 NF2 sample1 NF2 sample
- GSM8743877 NF2 sample2 NF2 sample
- GSM8743878 NF2 sample3 NF2 sample
- GSM8743879 NF2 sample4 NF2 sample
- GSM8743880 NF2 sample5 NF2 sample
- GSM8743881 NF2 sample6 NF2 sample
- GSM8743882 NF2 sample7 NF2 sample
- GSM8743883 NF2 sample8 NF2 sample
- GSM8743884 NF2 sample9 NF2 sample
- GSM8743885 BAP1 sample1 BAP1 sample
- GSM8743886 BAP1 sample2 BAP1 sample
- GSM8743887 BAP1 sample3 BAP1 sample
- GSM8743888 BAP1 sample4 BAP1 sample
- GSM8743889 BAP1 sample5 BAP1 sample
- GSM8743890 BAP1 sample6 BAP1 sample
- GSM8743891 BAP1 sample7 BAP1 sample
- GSM8743892 BAP1 sample8 BAP1 sample
- GSM8743893 BAP1 sample9 BAP1 sample
- GSM8743894 BAP1 sample10 BAP1 sample
- GSM8743895 BAP1 sample11 BAP1 sample
- GSM8743896 BAP1 sample12 BAP1 sample
- GSM8743897 BAP1 sample13 BAP1 sample
- GSM8743898 H3K27me3 loss sample1 H3K27me3 loss sample
- GSM8743899 H3K27me3 loss sample2 H3K27me3 loss sample
- GSM8743900 H3K27me3 loss sample3 H3K27me3 loss sample
- GSM8743901 H3K27me3 loss sample4 H3K27me3 loss sample
- GSM8743902 H3K27me3 loss sample5 H3K27me3 loss sample
- GSM8743903 H3K27me3 loss sample6 H3K27me3 loss sample
- GSM8743904 H3K27me3 loss sample7 H3K27me3 loss sample
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- GSE315442 Transcriptomic profiling reveals distinct molecular signatures among lesion types in hidradenitis suppurativa 48 samples shares signatures, distinct
- GSE253279 Single-Cell Gene Expression Profiling reveals distinct exhaustion and senescence signatures in T cells across various types of male infertility 15 samples shares signatures, distinct
- GSE280271 Deep sequencing of microRNA and total RNA reveals distinct microRNA-mRNA signatures that differentiate pancreatic neuroendocrine neoplasia from non-diseased pancreas tissue [RNA-seq] 13 samples shares signatures, distinct
- GSE298243 Single-Cell Profiling of DNA Methylation in Autism Spectrum Disorder Prefrontal Cortex Reveals Distinct Regulatory and Aging Signatures 49 samples shares signatures, distinct
- GSE280720 Functional characterization of Central Nervous System (CNS) and peripheral immune responses in Alzheimer's Disease after Bacillus Calmette Guerin (BCG) vaccination in older adults. 64 samples shares cns
- GSE299831 KOLF2.1J iTF-Microglia: A standardized platform to study microglial transcriptional regulatory networks in CNS disease [RNA-seq] 12 samples shares cns
- GSE73801 DNA methylation data from CNS-PNETs and various other brain tumor samples 593 samples shares cns
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.