Distinct differentiation trajectories leave lasting impacts on gene regulation and function of V2a neurons
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 60 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
- 60 samples: 20 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.
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 GSE283005_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 PRJNA1191434 and SRA study SRP546841. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 42 samples.
How we read this: 20 replicated groups read from 60 sample titles; they account for 42 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.
- GSM8646267 NEP, replicate 1, snRNA
- GSM8646268 NEP, replicate 2, snRNA
- GSM8646269 NMP, replicate 1, snRNA
- GSM8646270 NMP, replicate 2, snRNA
- GSM8646271 IND4, replicate 1, snRNA
- GSM8646272 IND10, replicate 1, snRNA
- GSM8648623 NEP, replicate 1, snATAC
- GSM8648624 NEP, replicate 2, snATAC
- GSM8648625 NMP, replicate 1, snATAC
- GSM8648626 NMP, replicate 2, snATAC
- GSM8648627 IND4, replicate 1, snATAC
- GSM8648628 IND10, replicate 1, snATAC
- GSM8651902 CREB5 KD, NEP, shRNA1, replicate1 CREB5 KD, NEP, shRNA1,
- GSM8651903 CREB5 KD, NEP, shRNA1, replicate2, reseq
- GSM8651904 CREB5 KD, NEP, shRNA1, replicate2 CREB5 KD, NEP, shRNA1,
- GSM8651905 CREB5 KD, NEP, shRNA2, replicate1 CREB5 KD, NEP, shRNA2,
- GSM8651906 CREB5 KD, NEP, shRNA2, replicate2 CREB5 KD, NEP, shRNA2,
- GSM8651907 CREB5 KD, NMP, shRNA1, replicate2
- GSM8651908 CREB5 KD, NMP, shRNA2, replicate1, reseq
- GSM8651909 CREB5 KD, NMP, shRNA2, replicate1 CREB5 KD, NMP, shRNA2,
- GSM8651910 CREB5 KD, NMP, shRNA2, replicate2 CREB5 KD, NMP, shRNA2,
- GSM8651911 CTL, NEP, replicate1 CTL, NEP,
- GSM8651912 CTL, NEP, replicate2 CTL, NEP,
- GSM8651913 CTL, NEP, replicate3 CTL, NEP,
- GSM8651914 CTL, NMP, replicate1 CTL, NMP,
- GSM8651915 CTL, NMP, replicate2 CTL, NMP,
- GSM8651916 CTL, NMP, replicate3 CTL, NMP,
- GSM8651917 KLF12 KD, NEP, shRNA1, replicate1 KLF12 KD, NEP, shRNA1,
- GSM8651918 KLF12 KD, NEP, shRNA1, replicate2 KLF12 KD, NEP, shRNA1,
- GSM8651919 KLF12 KD, NEP, shRNA2, replicate1 KLF12 KD, NEP, shRNA2,
- GSM8651920 KLF12 KD, NEP, shRNA2, replicate2 KLF12 KD, NEP, shRNA2,
- GSM8651921 KLF12 KD, NMP, shRNA1, replicate1 KLF12 KD, NMP, shRNA1,
- GSM8651922 KLF12 KD, NMP, shRNA1, replicate2 KLF12 KD, NMP, shRNA1,
- GSM8651923 KLF12 KD, NMP, shRNA2, replicate1 KLF12 KD, NMP, shRNA2,
- GSM8651924 KLF12 KD, NMP, shRNA2, replicate2 KLF12 KD, NMP, shRNA2,
- GSM8651925 ONECUT2 KD, NEP, shRNA1, replicate2
- GSM8651926 ONECUT2 KD, NEP, shRNA2, replicate1 ONECUT2 KD, NEP, shRNA2,
- GSM8651927 ONECUT2 KD, NEP, shRNA2, replicate2 ONECUT2 KD, NEP, shRNA2,
- GSM8651928 ONECUT2 KD, NMP, shRNA1, replicate1 ONECUT2 KD, NMP, shRNA1,
- GSM8651929 ONECUT2 KD, NMP, shRNA1, replicate2 ONECUT2 KD, NMP, shRNA1,
+ 20 more — browse all 60 samples with per-sample file links →
- GSE309967 Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes 48 samples shares trajectories, distinct
- GSE309941 Immunometabolic Endotypes Define Distinct Clinical Trajectories in Type 2 Diabetes [bulk RNA-seq] 42 samples shares trajectories, distinct
- GSE275610 scRNA-seq and snATAC-seq reveal differentiation trajectories of several pancreatic islet induction protocols 341 samples shares trajectories
- GSE332630 Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma 22 samples shares distinct
- GSE283832 A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories [Xenium Spatial_Transcriptomics] 7 samples shares trajectories
- GSE264443 Dynamic gene expression analysis reveals distinct severity phases of immune and cellular dysregulation in COVID-19 189 samples shares distinct
- GSE319130 Multi-omic analysis reveals molecular subtypes with distinct immunological phenotypes in SLE [RNA-Seq] 804 samples shares distinct
- GSE274284 Multi-omics dissection of human RAG deficiency reveals distinctive patterns of immune dysregulation but a common inflammatory signature 63 samples shares distinct
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.