Integrated multi-omics analysis
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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)
- Samples
- 10 samples: 3 × hiPS-CPC, high, biol vs 3 × hiPS-CPC, low, biol vs 2 × hiPS-CPC ATAC, high, biol vs 2 × hiPS-CPC ATAC, low, biolGroups 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
- Integrated multi-omics analysis identifies features that predict human pluripotent stem cell-derived progenitor differentiation to cardiomyocytesJournal of molecular and cellular cardiology · 2024
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 GSE254297_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 PRJNA1069651 and SRA study SRP486130. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 4 replicated groups read from 10 sample titles; they account for 10 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.
- GSM8037344 hiPS-CPC ATAC, high, biol rep1 hiPS-CPC ATAC, high, bi…
- GSM8037345 hiPS-CPC ATAC, high, biol rep2 hiPS-CPC ATAC, high, bi…
- GSM8037346 hiPS-CPC ATAC, low, biol rep1 hiPS-CPC ATAC, low, biol
- GSM8037347 hiPS-CPC ATAC, low, biol rep2 hiPS-CPC ATAC, low, biol
- GSM8037348 hiPS-CPC, high, biol rep1 hiPS-CPC, high, biol
- GSM8037349 hiPS-CPC, high, biol rep2 hiPS-CPC, high, biol
- GSM8037350 hiPS-CPC, high, biol rep3 hiPS-CPC, high, biol
- GSM8037351 hiPS-CPC, low, biol rep1 hiPS-CPC, low, biol
- GSM8037352 hiPS-CPC, low, biol rep2 hiPS-CPC, low, biol
- GSM8037353 hiPS-CPC, low, biol rep3 hiPS-CPC, low, biol
- GSE319092 Integrated Multi-Omics and Interactome Analysis of CDK8 Inhibition Reveals Erythroid Differentiation Programs and BET Synergy in AML Stem-like Cells 135 samples shares multi-omics, integrated
- GSE292721 Oxidative stress-regulatory role of miR-10b-5p in the diabetic human cornea revealed through integrated multi-omics analysis 16 samples shares multi-omics, integrated
- GSE265774 Integrated multi-omics single cell atlas of the human retina 63 samples shares multi-omics, integrated
- GSE237810 Multi-omics analysis of FOXO3 pioneer factor activity reveals distinct networks in proliferating and DNA damage induced senescent cells 65 samples shares multi-omics
- GSE283619 Single-cell multi-omics analysis identifies metabolism-linked epigenetic reprogramming as a driver of therapy-resistant medulloblastoma [Multiome] 30 samples shares multi-omics
- GSE335210 SOX9-BAF multi-omics profiling in human colon cancer cell models 173 samples shares multi-omics
- GSE330130 A multi-omics characterization of the human lumbar spinal cord and motor cortex reveals non-overlapping molecular signatures in ALS [snRNA-Seq; snATAC-Seq] 87 samples shares multi-omics
- GSE294559 Single-cell multi-omics characterize colorectal tumors, adjacent healthy tissue and matched organoids identifying CRC-unique features 72 samples shares multi-omics
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.