Regulation of sarcomere formation and function in the healthy heart requires a titin intronic enhancer.
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)
- Samples
- 32 samples: 11 conditions, mostly in duplicateGroups 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
- Regulation of sarcomere formation and function in the healthy heart requires a titin intronic enhancerThe Journal of clinical investigation · 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 GSE283867_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 PRJNA1195932 and SRA study SRP547161. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 28 samples.
How we read this: 11 replicated groups read from 32 sample titles; they account for 28 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.
- GSM8648629 E0del/+_LV_1 E0del/+_LV
- GSM8648630 E0del/+_SkM_1 E0del/+_SkM
- GSM8648631 WT_LV_1 WT_LV
- GSM8648632 WT_SkM_1 WT_SkM
- GSM8648633 E0del/+_LV_2 E0del/+_LV
- GSM8648634 E0del/+_SkM_2 E0del/+_SkM
- GSM8648635 WT_LV_2 WT_LV
- GSM8648636 WT_SkM_2 WT_SkM
- GSM8648637 E0del/+_LV_3 E0del/+_LV
- GSM8648638 E0del/+_SkM_3 E0del/+_SkM
- GSM8648866 Pooled snRNAseq of WT and MEF2_T>C CMs 1 Pooled snRNAseq of WT a…
- GSM8648867 Pooled snRNAseq of WT and MEF2_T>C CMs 2 Pooled snRNAseq of WT a…
- GSM8648868 Pooled snRNAseq of WT and E1 deletion CMs
- GSM8648869 Pooled snRNAseq of WT and E0 deletion CMs
- GSM8648870 Lipid Oligo Barcode library of WT and MEF2_T>C CMs 1 Lipid Oligo Barcode lib…
- GSM8648871 Lipid Oligo Barcode library of WT and MEF2_T>C CMs 2 Lipid Oligo Barcode lib…
- GSM8648872 Lipid Oligo Barcode library of WT and E1 deletion CMs
- GSM8648873 Lipid Oligo Barcode library of WT and E0 deletion CMs
- GSM8673590 ATACseq of D0 hiPSCs Rep1 ATACseq of D0 hiPSCs
- GSM8673591 ATACseq of D0 hiPSCs Rep2 ATACseq of D0 hiPSCs
- GSM8673592 ATACseq of D4 hiPSC-CMs Rep1 ATACseq of D4 hiPSC-CMs
- GSM8673593 ATACseq of D4 hiPSC-CMs Rep2 ATACseq of D4 hiPSC-CMs
- GSM8673594 ATACseq of D8 hiPSC-CMs Rep1 ATACseq of D8 hiPSC-CMs
- GSM8673595 ATACseq of D8 hiPSC-CMs Rep2 ATACseq of D8 hiPSC-CMs
- GSM8673596 ATACseq of D17 hiPSC-CMs Rep1 ATACseq of D17 hiPSC-CMs
- GSM8673597 ATACseq of D17 hiPSC-CMs Rep2 ATACseq of D17 hiPSC-CMs
- GSM8673598 ATACseq of D17 hiPSC-CMs Rep3 ATACseq of D17 hiPSC-CMs
- GSM8673599 ATACseq of D17 hiPSC-CMs Rep4 ATACseq of D17 hiPSC-CMs
- GSM8673600 ATACseq of D30 hiPSC-CMs Rep1 ATACseq of D30 hiPSC-CMs
- GSM8673601 ATACseq of D30 hiPSC-CMs Rep2 ATACseq of D30 hiPSC-CMs
- GSM8673602 ATACseq of D30 hiPSC-CMs Rep3 ATACseq of D30 hiPSC-CMs
- GSM8673603 ATACseq of D30 hiPSC-CMs Rep4 ATACseq of D30 hiPSC-CMs
- GSE253716 IRF4 requires ARID1A to establish plasma cell identity in multiple myeloma 99 samples shares requires
- GSE309285 CK2-mediated DEK Phosphorylation Drives PBX3 Overexpression: A Core Event in Hematopoietic Stem Cell-to-Leukemia Stem Cell Transformation 53 samples shares formation
- GSE312944 Inhibition of METTL3 by STC-15 induces RNA misprocessing that results in dsRNA formation and activates innate immunity 140 samples shares formation
- GSE250345 Functional inhibition of core spliceosomal machinery activates intronic premature cleavage and polyadenylation of pre-mRNAs 92 samples shares intronic
- GSE78109 Pathogenicity of genomic duplications is determined by formation of novel chromatin domains (neo-TADs) 48 samples shares formation
- GSE307527 ARID1A and ARID1B preserve B cell identity, prevent myeloid transformation and reveal therapeutic vulnerabilities 30 samples shares formation
- GSE264696 Cytokines drive the formation of memory-like NK cell subsets via epigenetic rewiring and transcriptional mechanisms [CITE-seq] 16 samples shares formation
- GSE281868 Identification of epigenetic regulators of fibrotic transformation in cardiac fibroblasts through bulk and single-cell CRISPR screens (ATAC-Seq_2) 12 samples shares formation
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.