Spatially-Resolved Multiomic Atlas of Leiomyosarcoma Identifies Two Clinically Relevant Epigenetically-Driven Cell States [scMultiomic]
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 32 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
- Soft tissue sarcomaThis series is part of our curated briefing on it.
- Samples
- 32 samples: 32 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.
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 GSE324206_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 PRJNA1372071. 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 32 sample titles: 32 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.
- GSM9571057 scMultiomic RNA-Seq of LMS, 107168_9 (Batch 1)
- GSM9571059 scMultiomic RNA-Seq of LMS, 768869_7 (Batch1)
- GSM9571061 scMultiomic RNA-Seq of LMS, 1242796_12 (Batch1)
- GSM9571063 scMultiomic RNA-Seq of LMS, 1532950_8 (Batch1)
- GSM9571065 scMultiomic RNA-Seq of LMS, 133209_6 (Batch2)
- GSM9571067 scMultiomic RNA-Seq of LMS, 890688_1 (Batch2)
- GSM9571069 scMultiomic RNA-Seq of LMS, 986219_11 (Batch2)
- GSM9571071 scMultiomic RNA-Seq of LMS, 989922_9 (Batch2)
- GSM9571073 scMultiomic RNA-Seq of LMS, 1007170_8 (Batch2)
- GSM9571075 scMultiomic RNA-Seq of LMS, 1109587_2 (Batch2)
- GSM9571077 scMultiomic RNA-Seq of LMS, 1311956_7 (Batch2)
- GSM9571079 scMultiomic RNA-Seq of LMS, 1424298_3 (Batch2)
- GSM9571081 scMultiomic RNA-Seq of LMS, 13_085 (Batch3)
- GSM9571083 scMultiomic RNA-Seq of LMS, 17_494 (Batch3)
- GSM9571085 scMultiomic RNA-Seq of LMS, 18_049 (Batch3)
- GSM9571087 scMultiomic RNA-Seq of LMS, 18_411 (Batch3)
- GSM9571089 scMultiomic ATAC-Seq of LMS,107168_9 (Batch1)
- GSM9571091 scMultiomic ATAC-Seq of LMS, 768869_7 (Batch1)
- GSM9571093 scMultiomic ATAC-Seq of LMS, 1242796_12 (Batch1)
- GSM9571095 scMultiomic ATAC-Seq of LMS, 1532950_8 (Batch1)
- GSM9571097 scMultiomic ATAC-Seq of LMS, 133209_6 (Batch2)
- GSM9571099 scMultiomic ATAC-Seq of LMS, 890688_1 (Batch2)
- GSM9571101 scMultiomic ATAC-Seq of LMS, 986219_11 (Batch2)
- GSM9571103 scMultiomic ATAC-Seq of LMS, 989922_9 (Batch2)
- GSM9571105 scMultiomic ATAC-Seq of LMS, 1007170_8 (Batch2)
- GSM9571107 scMultiomic ATAC-Seq of LMS, 1109587_2 (Batch2)
- GSM9571110 scMultiomic ATAC-Seq of LMS, 1311956_7 (Batch2)
- GSM9571112 scMultiomic ATAC-Seq of LMS, 1424298_3 (Batch2)
- GSM9571114 scMultiomic ATAC-Seq of LMS, 13_085 (Batch3)
- GSM9571116 scMultiomic ATAC-Seq of LMS, 17_494 (Batch3)
- GSM9571118 scMultiomic ATAC-Seq of LMS, 18_049 (Batch3)
- GSM9571120 scMultiomic ATAC-Seq of LMS, 18_411 (Batch3)
- GSE287694 Integration of whole genome sequencing analysis with unique patient-derived models reveals clinically relevant drug targets in TFCP2 fusion-defined intraosseous rhabdomyosarcoma 2 samples same disease briefing · shares clinically, relevant
- GSE274640 MYOD1L122R induces cancer stem cell pathways to impart chemotherapy and radiation-resistance in aggressive rhabdomyosarcoma. 80 samples same disease briefing
- GSE279337 Dependence of PAX3-FOXO1 chromatin occupancy on ETS1 at important disease-promoting genes exposes new targetable vulnerability in Fusion-Positive Rhabdomyosarcoma 40 samples same disease briefing
- GSE276201 A multitargeting approach rewires cell identity in fusion-negative rhabdomyosarcoma 28 samples same disease briefing
- GSE312030 Combined inhibition of HRAS and MEK induces tumor regression and restores myogenic differentiation in HRAS-mutant rhabdomyosarcoma 159 samples same disease briefing
- GSE303028 CDK8 Inhibition Releases the Muscle Differentiation Blockade in Fusion-driven Alveolar Rhabdomyosarcoma 104 samples same disease briefing
- GSE273829 GABA promotes resistance to immunotherapy of patients with TLS-positive tumors [RNA-seq] 92 samples same disease briefing
- GSE253895 PAX translocations remodel mitochondrial metabolism through altered leucine usage in rhabdomyosarcoma 58 samples same disease briefing
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.