FeaSion Decodes the Regulatory Landscape and Functional Diversity of RNA Polymerase II CTD Phosphorylation
RNA-seq (gene expression) · human · 30 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 30 samples: 15 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 GSE287315_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1211534 and SRA study SRP557876. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 30 samples.
How we read this: 15 replicated groups read from 30 sample titles; they account for 30 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
- GSE287535 FeaSion Decodes the Regulatory Landscape and Functional Diversity of RNA Polymerase II CTD Phosphorylation 225 samples shares ctd, phosphorylation, regulatory, polymerase, diversity, feasion, decodes
- 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
- GSE261258 Human regulatory memory B cells defined by expression of TIM-1 and TIGIT are dysfunctional in Multiple Sclerosis. 89 samples shares regulatory
- GSE256068 Identification of gene regulatory networks affected across drug-resistant epilepsies 162 samples shares regulatory
- GSE303045 Single Cell Multiomics Across Nine Mammals Reveals Cell Type Specific Regulatory Conservation in the Brain 132 samples shares regulatory
- GSE298578 Single cell RNA profiling of blood CD4+ T cells identifies distinct helper and dysfunctional regulatory clusters in children with SLE (5' PBMC validation dataset) 14 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.