FeaSion Decodes the Regulatory Landscape and Functional Diversity of RNA Polymerase II CTD Phosphorylation
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 225 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
- 225 samples: 112 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
- FeaSion decodes the regulatory landscape and functional diversity of RNA polymerase II CTD phosphorylationScience advances · 2025
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 GSE287535_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 PRJNA1213690. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 224 samples.
How we read this: 112 replicated groups read from 225 sample titles; they account for 224 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.
- GSM8743674 RNA-seq_Mock_rep1 RNA-seq_Mock
- GSM8743675 RNA-seq_Mock_rep2 RNA-seq_Mock
- GSM8743676 RNA-seq_Degron_RPB1_dTAG_0h_rep1 RNA-seq_Degron_RPB1_dTA…
- GSM8743677 RNA-seq_Degron_RPB1_dTAG_0h_rep2 RNA-seq_Degron_RPB1_dTA…
- GSM8743678 RNA-seq_Degron_RPB1_dTAG_12h_rep1 RNA-seq_Degron_RPB1_dTA…
- GSM8743679 RNA-seq_Degron_RPB1_dTAG_12h_rep2 RNA-seq_Degron_RPB1_dTA…
- GSM8743680 RNA-seq_WT_dTAG_0h_rep1 RNA-seq_WT_dTAG_0h
- GSM8743681 RNA-seq_WT_dTAG_0h_rep2 RNA-seq_WT_dTAG_0h
- GSM8743682 RNA-seq_WT_dTAG_12h_rep1 RNA-seq_WT_dTAG_12h
- GSM8743683 RNA-seq_WT_dTAG_12h_rep2 RNA-seq_WT_dTAG_12h
- GSM8743684 RNA-seq_Y1F_dTAG_0h_rep1 RNA-seq_Y1F_dTAG_0h
- GSM8743685 RNA-seq_Y1F_dTAG_0h_rep2 RNA-seq_Y1F_dTAG_0h
- GSM8743686 RNA-seq_Y1F_dTAG_12h_rep1 RNA-seq_Y1F_dTAG_12h
- GSM8743687 RNA-seq_Y1F_dTAG_12h_rep2 RNA-seq_Y1F_dTAG_12h
- GSM8743688 RNA-seq_S2A_dTAG_0h_rep1 RNA-seq_S2A_dTAG_0h
- GSM8743689 RNA-seq_S2A_dTAG_0h_rep2 RNA-seq_S2A_dTAG_0h
- GSM8743690 RNA-seq_S2A_dTAG_12h_rep1 RNA-seq_S2A_dTAG_12h
- GSM8743691 RNA-seq_S2A_dTAG_12h_rep2 RNA-seq_S2A_dTAG_12h
- GSM8743692 RNA-seq_T4V_dTAG_0h_rep1 RNA-seq_T4V_dTAG_0h
- GSM8743693 RNA-seq_T4V_dTAG_0h_rep2 RNA-seq_T4V_dTAG_0h
- GSM8743694 RNA-seq_T4V_dTAG_12h_rep1 RNA-seq_T4V_dTAG_12h
- GSM8743695 RNA-seq_T4V_dTAG_12h_rep2 RNA-seq_T4V_dTAG_12h
- GSM8743696 RNA-seq_S5A_dTAG_0h_rep1 RNA-seq_S5A_dTAG_0h
- GSM8743697 RNA-seq_S5A_dTAG_0h_rep2 RNA-seq_S5A_dTAG_0h
- GSM8743698 RNA-seq_S5A_dTAG_12h_rep1 RNA-seq_S5A_dTAG_12h
- GSM8743699 RNA-seq_S5A_dTAG_12h_rep2 RNA-seq_S5A_dTAG_12h
- GSM8743700 RNA-seq_S7A_dTAG_0h_rep1 RNA-seq_S7A_dTAG_0h
- GSM8743701 RNA-seq_S7A_dTAG_0h_rep2 RNA-seq_S7A_dTAG_0h
- GSM8743702 RNA-seq_S7A_dTAG_12h_rep1 RNA-seq_S7A_dTAG_12h
- GSM8743703 RNA-seq_S7A_dTAG_12h_rep2 RNA-seq_S7A_dTAG_12h
- GSM8743704 ChIP-seq_Input
- GSM8743705 ChIP-seq_RNAPII_rep1 ChIP-seq_RNAPII
- GSM8743706 ChIP-seq_RNAPII_rep2 ChIP-seq_RNAPII
- GSM8743707 ChIP-seq_pY1_rep1 ChIP-seq_pY1
- GSM8743708 ChIP-seq_pY1_rep2 ChIP-seq_pY1
- GSM8743709 ChIP-seq_pS2_rep1 ChIP-seq_pS2
- GSM8743710 ChIP-seq_pS2_rep2 ChIP-seq_pS2
- GSM8743711 ChIP-seq_pT4_rep1 ChIP-seq_pT4
- GSM8743712 ChIP-seq_pT4_rep2 ChIP-seq_pT4
- GSM8743713 ChIP-seq_pS5_rep1 ChIP-seq_pS5
+ 185 more — browse all 225 samples with per-sample file links →
- GSE325942 Decoding a combinatorial RNA polymerase II CTD grammar that specifies protein-coding gene transcription and mRNA export 24 samples shares ctd, polymerase
- GSE265883 Tripartite phosphorylation of SPT5 by CDK9 times pause release and tunes elongation rate of RNA polymerase II (CUT&RUN) 68 samples shares phosphorylation, polymerase
- GSE306294 An RNA polymerase III tissue and tumor atlas uncovers context-specific activities linked to 3D epigenome regulatory mechanisms 24 samples shares regulatory, polymerase
- GSE336415 ZFP36L2 orchestrates stress-adaptive plasticity in intestinal regeneration and colorectal cancer metastasis (ActDseq) 24 samples shares ctd
- GSE327101 Single-Cell Multimodal Atlas Reveals Regulatory Programs in the Human Brain 220 samples shares regulatory
- GSE218269 CDK7 kinase activity promotes RNA polymerase II promoter escape by facilitating initiation factor release 100 samples shares polymerase
- GSE272082 Single-nucleus multiomics reveals the regulatory programs in three brain regions of sporadic early-onset Alzheimer's Disease 42 samples shares regulatory
- GSE243526 Defining the Regulatory Logic of Breast Cancer Using Single-Cell Epigenetic and Transcriptome Profiling 40 samples shares regulatory
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.