Hmgb2 improves astrocyte to neuron conversion by increasing the chromatin accessibility of genes associated with neuronal maturation in a proneuronal factor-dependent manner[RNA-Seq]
RNA-seq (gene expression) · mouse · 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
- Mus musculus (mouse)
- Samples
- 29 samples: 29 samples, each with a distinct title — no replicated groupsGroups 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
- Hmgb2 improves astrocyte to neuron conversion by increasing the chromatin accessibility of genes associated with neuronal maturation in a proneuronal factor-dependent mannerGenome biology · 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 GSE240857_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 PRJNA1005587 and SRA study SRP455145. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 29 sample titles: 29 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.
- GSM7710782 EGF_FGF_Control_1 [RNA-Seq]
- GSM7710783 EGF_FGF_Control_2 [RNA-Seq]
- GSM7710784 EGF_FGF_Control_3 [RNA-Seq]
- GSM7710785 EGF_FGF_Control_4 [RNA-Seq]
- GSM7710786 EGF_FGF_Control_5 [RNA-Seq]
- GSM7710787 EGF_FGF_Neurog2_1 [RNA-Seq]
- GSM7710788 EGF_FGF_Neurog2_2 [RNA-Seq]
- GSM7710789 EGF_FGF_Neurog2_3 [RNA-Seq]
- GSM7710790 EGF_FGF_Neurog2_Hmgb2_1 [RNA-Seq]
- GSM7710791 EGF_FGF_Neurog2_Hmgb2_2 [RNA-Seq]
- GSM7710792 EGF_FGF_Neurog2_Hmgb2_3 [RNA-Seq]
- GSM7710793 EGF_FGF_Hmgb2_1 [RNA-Seq]
- GSM7710794 EGF_FGF_Hmgb2_2 [RNA-Seq]
- GSM7710795 EGF_FGF_Hmgb2_3 [RNA-Seq]
- GSM7710796 EGF_FGF_Hmgb2_4 [RNA-Seq]
- GSM7710797 FGF_Control_1 [RNA-Seq]
- GSM7710798 FGF_Control_2 [RNA-Seq]
- GSM7710799 FGF_Control_3 [RNA-Seq]
- GSM7710800 FGF_Hmgb2_1 [RNA-Seq]
- GSM7710801 FGF_Hmgb2_2 [RNA-Seq]
- GSM7710802 FGF_Hmgb2_3 [RNA-Seq]
- GSM7710803 FGF_Hmgb2_4 [RNA-Seq]
- GSM7710804 FGF_Neurog2_Hmgb2_1 [RNA-Seq]
- GSM7710805 FGF_Neurog2_Hmgb2_2 [RNA-Seq]
- GSM7710806 FGF_Neurog2_Hmgb2_3 [RNA-Seq]
- GSM7710807 FGF_Neurog2_1 [RNA-Seq]
- GSM7710808 FGF_Neurog2_2 [RNA-Seq]
- GSM7710809 FGF_Neurog2_3 [RNA-Seq]
- GSM7710810 FGF_Neurog2_4 [RNA-Seq]
- GSE240860 Hmgb2 improves astrocyte to neuron conversion by increasing the chromatin accessibility of genes associated with neuronal maturation in a proneuronal factor-dependent manner 54 samples shares hmgb2, factor-dependent, accessibility, proneuronal, conversion, increasing, maturation, astrocyte
- GSE240782 Hmgb2 improves astrocyte to neuron conversion by increasing the chromatin accessibility of genes associated with neuronal maturation in a proneuronal factor-dependent manner [ATAC-Seq] 25 samples shares hmgb2, factor-dependent, accessibility, proneuronal, conversion, increasing, maturation, astrocyte
- GSE227933 Dendritic Cell maturation/migration is architected by chromatin accessibility and a tonic organismal IFNgR1 response gradient which governs immune priming and tolerance 32 samples shares accessibility, maturation
- GSE290224 Intermittent Fasting Reprograms Chromatin Accessibility to Modulate Gene Expression in Brain and Muscle 96 samples shares accessibility
- GSE246701 Regulatory T cells in the Tumor Microenvironment Display a Unique Chromatin Accessibility Profile (RNA-Seq) 64 samples shares accessibility
- GSE276261 EOMES safeguards TSC chromatin accessibility by directing BRG1 to TSC-associated loci [RNA-seq] 45 samples shares accessibility
- GSE278050 KLF13 promotes SLE Pathogenesis by modifying chromatin accessibility of key proinflammatory cytokine genes [RNA-seq] 42 samples shares accessibility
- GSE234248 Systematic assessment of ISWI subunits reveals that NURF creates local accessibility for CTCF [RNA-seq] 24 samples shares accessibility
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.