Open chromatin, HIF binding and mRNA expression analysis in primary tubule and ccRCC cells [RNA-seq]
RNA-seq (gene expression) · human · 32 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
- 32 samples: 16 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
- HIF sustain a transcriptional regulatory circuit of EPAS1 expression in renal clear cell carcinomaNature communications · 2026
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 GSE256000_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 PRJNA1077373 and SRA study SRP490101. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 32 samples.
How we read this: 16 replicated groups read from 32 sample titles; they account for 32 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.
- GSM8083996 RNA_PTC_ctrl_1_rep_1 RNA_PTC_ctrl_1
- GSM8083997 RNA_PTC_ctrl_1_rep_2 RNA_PTC_ctrl_1
- GSM8083998 RNA_PTC_ctrl_2_rep_1 RNA_PTC_ctrl_2
- GSM8083999 RNA_PTC_ctrl_2_rep_2 RNA_PTC_ctrl_2
- GSM8084000 RNA_PTC_ctrl_3_rep_1 RNA_PTC_ctrl_3
- GSM8084001 RNA_PTC_ctrl_3_rep_2 RNA_PTC_ctrl_3
- GSM8084002 RNA_ccRCC_ctrl_1_rep_1 RNA_ccRCC_ctrl_1
- GSM8084003 RNA_ccRCC_ctrl_1_rep_2 RNA_ccRCC_ctrl_1
- GSM8084004 RNA_ccRCC_ctrl_2_rep_1 RNA_ccRCC_ctrl_2
- GSM8084005 RNA_ccRCC_ctrl_2_rep_2 RNA_ccRCC_ctrl_2
- GSM8084006 RNA_ccRCC_ctrl_3_rep_1 RNA_ccRCC_ctrl_3
- GSM8084007 RNA_ccRCC_ctrl_3_rep_2 RNA_ccRCC_ctrl_3
- GSM8084008 RNA_760_pool_nt_rep_1 RNA_760_pool_nt
- GSM8084009 RNA_760_pool_nt_rep_2 RNA_760_pool_nt
- GSM8084010 RNA_760_pool_E2_ko_rep_1 RNA_760_pool_E2_ko
- GSM8084011 RNA_760_pool_E2_ko_rep_2 RNA_760_pool_E2_ko
- GSM8084012 RNA_RCC4_pool_nt_rep_1 RNA_RCC4_pool_nt
- GSM8084013 RNA_RCC4_pool_nt_rep_2 RNA_RCC4_pool_nt
- GSM8084014 RNA_RCC4_pool_E2_ko_rep_1 RNA_RCC4_pool_E2_ko
- GSM8084015 RNA_RCC4_pool_E2_ko_rep_2 RNA_RCC4_pool_E2_ko
- GSM8084024 RNA_U87_ctrl_rep_1 RNA_U87_ctrl
- GSM8084025 RNA_U87_ctrl_rep_2 RNA_U87_ctrl
- GSM8084026 RNA_U87_DMOG_rep_1 RNA_U87_DMOG
- GSM8084027 RNA_U87_DMOG_rep_2 RNA_U87_DMOG
- GSM8695635 RNA_7860_clone_nt_3_rep_1 RNA_7860_clone_nt_3
- GSM8695636 RNA_7860_clone_nt_3_rep_2 RNA_7860_clone_nt_3
- GSM8695637 RNA_7860_clone_nt_5_rep_1 RNA_7860_clone_nt_5
- GSM8695638 RNA_7860_clone_nt_5_rep_2 RNA_7860_clone_nt_5
- GSM8695639 RNA_7860_clone_E2_HIFko_6_rep_1 RNA_7860_clone_E2_HIFko…
- GSM8695640 RNA_7860_clone_E2_HIFko_6_rep_2 RNA_7860_clone_E2_HIFko…
- GSM8695641 RNA_7860_clone_E2_HIFko_7_rep_1 RNA_7860_clone_E2_HIFko…
- GSM8695642 RNA_7860_clone_E2_HIFko_7_rep_2 RNA_7860_clone_E2_HIFko…
- GSE301512 Chromatin topology dynamics of dexamethasone-treated trabecular meshwork identifies 78 causal genes for intraocular pressure and primary open angle glaucoma [CUT&Run] 30 samples shares chromatin, primary, open
- GSE205154 Bulk RNA-Seq gene expression data for 289 primary and metastatic pancreatic ductal adenocarcinoma (PDAC) tumor samples from FFPE blocks. 289 samples shares primary, rna-seq
- GSE297742 Bulk RNA-seq of primary tumor biopsy samples from prostate adenocarcinoma patients 234 samples shares primary, rna-seq
- GSE327289 Cerebrovascular Single-Nucleus RNA-Seq Reveals Heat Shock Activation and Vascular Remodeling in Alzheimer’s Disease and Primary Tauopathies 76 samples shares primary, rna-seq
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares primary, rna-seq
- GSE337246 Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer [scRNA-Seq organoids] 35 samples shares chromatin, rna-seq
- GSE339484 RNA-seq profiling of 14 paired primary and recurrent glioma cases 28 samples shares primary, rna-seq
- GSE327352 Virus-like particles enable targeted gene engineering and pooled CRISPR screening in primary human myeloid cells [RNA-seq Exp2] 12 samples shares primary, rna-seq
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.