Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 35 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
- 35 samples: 12 conditions, mostly in triplicateGroups 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
- Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-CDiabetologia · 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 GSE262484_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 PRJNA1091957 and SRA study SRP497916. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 33 samples.
How we read this: 12 replicated groups read from 35 sample titles; they account for 33 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.
- GSM8170378 EndoC-BH1 ATAC-Seq replicate 1 EndoC-BH1 ATAC-Seq
- GSM8170379 EndoC-BH1 ATAC-Seq replicate 2 EndoC-BH1 ATAC-Seq
- GSM8170380 EndoC-BH1 ATAC-Seq replicate 3 EndoC-BH1 ATAC-Seq
- GSM8170381 SGBS Differentiated ATAC-Seq replicate 1 SGBS Differentiated ATA…
- GSM8170382 SGBS Differentiated ATAC-Seq replicate 2 SGBS Differentiated ATA…
- GSM8170383 SGBS Differentiated ATAC-Seq replicate 3 SGBS Differentiated ATA…
- GSM8170384 SGBS Undifferentiated ATAC-Seq replicate 1 SGBS Undifferentiated A…
- GSM8170385 SGBS Undifferentiated ATAC-Seq replicate 2 SGBS Undifferentiated A…
- GSM8170386 SGBS Undifferentiated ATAC-Seq replicate 3 SGBS Undifferentiated A…
- GSM8170387 HEPG2 ATAC-Seq replicate 1 HEPG2 ATAC-Seq
- GSM8170388 HEPG2 ATAC-Seq replicate 2 HEPG2 ATAC-Seq
- GSM8170389 HEPG2 ATAC-Seq replicate 3 HEPG2 ATAC-Seq
- GSM8170390 EndoC-BH1 RNA-Seq replicate 1 EndoC-BH1 RNA-Seq
- GSM8170391 EndoC-BH1 RNA-Seq replicate 2 EndoC-BH1 RNA-Seq
- GSM8170392 EndoC-BH1 RNA-Seq replicate 3 EndoC-BH1 RNA-Seq
- GSM8170393 SGBS Differentiated RNA-Seq replicate 1 SGBS Differentiated RNA…
- GSM8170394 SGBS Differentiated RNA-Seq replicate 2 SGBS Differentiated RNA…
- GSM8170395 SGBS Undifferentiated RNA-Seq replicate 1 SGBS Undifferentiated R…
- GSM8170396 SGBS Undifferentiated RNA-Seq replicate 2 SGBS Undifferentiated R…
- GSM8170397 HEPG2 RNA-Seq replicate 1 HEPG2 RNA-Seq
- GSM8170398 HEPG2 RNA-Seq replicate 2 HEPG2 RNA-Seq
- GSM8170399 HEPG2 RNA-Seq replicate 3 HEPG2 RNA-Seq
- GSM8170400 EndoC-BH1 Hi-C replicate A, technical replicate 1
- GSM8170401 EndoC-BH1 Hi-C replicate B, technical replicate 1
- GSM8170508 EndoC-BH1 replicate 1 EndoC-BH1
- GSM8170509 EndoC-BH1 replicate 2 EndoC-BH1
- GSM8170510 EndoC-BH1 replicate 3 EndoC-BH1
- GSM8170511 SGBS Differentiated replicate 1 SGBS Differentiated
- GSM8170512 SGBS Differentiated replicate 2 SGBS Differentiated
- GSM8170513 SGBS Differentiated replicate 3 SGBS Differentiated
- GSM8170514 SGBS Undifferentiated replicate 1 SGBS Undifferentiated
- GSM8170515 SGBS Undifferentiated replicate 2 SGBS Undifferentiated
- GSM8170516 SGBS Undifferentiated replicate 3 SGBS Undifferentiated
- GSM8170517 HEPG2 replicate 1 HEPG2
- GSM8170518 HEPG2 replicate 2 HEPG2
- GSE262479 Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C [ATAC-Seq] 12 samples shares promoter-focused, implicating, capture-c, diabetes, effector, relevant, cellular, type
- GSE262496 Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C [Capture-C] 11 samples shares promoter-focused, implicating, capture-c, diabetes, effector, relevant, cellular, type
- GSE262480 Implicating type 2 diabetes effector genes in relevant metabolic cellular models using promoter-focused Capture-C [RNA-Seq] 10 samples shares promoter-focused, implicating, capture-c, diabetes, effector, relevant, cellular, type
- GSE255566 Single-cell RNA sequencing of peripheral blood mononuclear cells reveals complex cellular signalling signatures of type 2 diabetes mellitus 8 samples shares diabetes, cellular, type
- GSE81608 RNA Sequencing of Single Human Islet Cells Reveals Type 2 Diabetes Genes 1600 samples shares diabetes, type
- GSE86473 Single cell transcriptomics defines human islet cell signatures and reveals cell-type-specific expression changes in type 2 diabetes 662 samples shares diabetes, type
- GSE86469 Single cell transcriptomics defines human islet cell signatures and reveals cell-type-specific expression changes in type 2 diabetes [single cell] 638 samples shares diabetes, type
- GSE314188 Responders to low-dose ATG induce CD4+ T cell exhaustion in type 1 diabetes 514 samples shares diabetes, type
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.