A Compendium of Chromatin Contact Maps Reveal Spatially Active Regions in the Human Genome
RNA-seq (gene expression) · mouse · 19 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
- 19 samples: 15 distinct titles, 3 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.
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 GSE87112_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 PRJNA343608 and SRA study SRP090175. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 19 sample titles: 15 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.
- GSM2322539 STL002_Adrenal Rep1
- GSM2322540 STL001_Bladder Rep1
- GSM2322541 STL001_Bladder Rep2
- GSM2322542 Dorsolateral Prefrontal Cortex
- GSM2322543 Hippocampus
- GSM2322544 STL002_Lung Rep1
- GSM2322545 STL001_Lung Rep1
- GSM2322546 STL002_Ovary Rep1
- GSM2322547 STL002_Pancreas Rep1
- GSM2322548 STL003_Pancreas Rep1
- GSM2322549 STL003_Pancreas Rep2
- GSM2322550 STL003_Pancreas Rep3
- GSM2322551 STL003_Psoas Rep1
- GSM2322552 STL001_Psoas Rep1
- GSM2322553 STL001_Psoas Rep2
- GSM2322554 STL003_RightVentricle Rep1
- GSM2322555 STL002_SmallBowel Rep1
- GSM2322556 STL003_Spleen Rep1
- GSM2322557 STL001_Spleen Rep1
- GSE304363 Paraspeckle Protein NONO Regulates Active Chromatin by Allosterically Stimulating NSD1 36 samples shares chromatin, active
- GSE288178 Spatially resolving chromatin landscapes in formalin-fixed paraffin-embedded tissues 9 samples shares chromatin, spatially
- GSE246859 ChromaFold predicts the 3D contact map from single-cell chromatin accessibility 3 samples shares chromatin, contact
- GSE243065 Minimizing far-extending chromatin perturbation in genome editing preserves stem cell identity 783 samples shares chromatin
- GSE278068 Nanobody-tethered transposition for dual profiling of chromatin accessibility and DNA methylation 201 samples shares chromatin
- GSE226003 Disruption of RNAPII transcription elongation links Oncogenic splicing factor mutations to replciation stress and targetable alterations in chromatin landscape. 170 samples shares chromatin
- GSE281919 LBR and LAP2 mediate heterochromatin tethering to the nuclear periphery to preserve genome homeostasis 111 samples shares chromatin
- GSE305653 Genome-wide chromatin recording resolves dynamic cell state changes 110 samples shares chromatin
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.