Effect of the sGC activator BAY 60-2770 on human proximal tubular (HK-2) cells under hypoxia and after TGF-β1 treatment
RNA-seq (gene expression) · human · 24 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
- 24 samples: 24 samples, each with a distinct title — no replicated groupsGroups 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.
Read the full summary ↓
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 GSE269418_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 PRJNA1121890 and SRA study SRP512757. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 24 sample titles: 24 distinct titles with little repetition. 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.
- GSM8315280 HK2 cells, normoxia, sGC activator, biol rep 1, RNA 01
- GSM8315281 HK2 cells, normoxia, sGC activator, biol rep 2, RNA 02
- GSM8315282 HK2 cells, normoxia, sGC activator, biol rep 3, RNA 03
- GSM8315283 HK2 cells, normoxia, solvent control, biol rep 1, RNA 04
- GSM8315284 HK2 cells, normoxia, solvent control, biol rep 2, RNA 05
- GSM8315285 HK2 cells, normoxia, solvent control, biol rep 3, RNA 06
- GSM8315286 HK2 cells, normoxia, solvent control, biol rep 4, RNA 07
- GSM8315287 HK2 cells, normoxia, TGF-β1, biol rep 1, RNA 08
- GSM8315288 HK2 cells, normoxia, TGF-β1, biol rep 2, RNA 09
- GSM8315289 HK2 cells, normoxia, TGF-β1, biol rep 3, RNA 10
- GSM8315290 HK2 cells, normoxia, TGF-β1, biol rep 4, RNA 11
- GSM8315291 HK2 cells, normoxia, TGF-β1, biol rep 5, RNA 12
- GSM8315292 HK2 cells, normoxia, TGF-β1+ sGC activator, biol rep 1, RNA 13
- GSM8315293 HK2 cells, normoxia, TGF-β1+ sGC activator, biol rep 2, RNA 14
- GSM8315294 HK2 cells, normoxia, TGF-β1+ sGC activator, biol rep 3, RNA 15
- GSM8315295 HK2 cells, normoxia, TGF-β1+ sGC activator, biol rep 4, RNA 16
- GSM8315296 HK2 cells, normoxia, TGF-β1+ sGC activator, biol rep 5, RNA 17
- GSM8315297 HK2 cells, normoxia, solvent control, biol rep 5, RNA 18
- GSM8315298 HK2 cells, hypoxia, sGC activator, biol rep 1, RNA 21
- GSM8315299 HK2 cells, hypoxia, sGC activator, biol rep 2, RNA 22
- GSM8315300 HK2 cells, hypoxia, sGC activator, biol rep 3, RNA 23
- GSM8315301 HK2 cells, hypoxia, solvent control, biol rep 1, RNA 31
- GSM8315302 HK2 cells, hypoxia, solvent control, biol rep 2, RNA 32
- GSM8315303 HK2 cells, hypoxia, solvent control, biol rep 3, RNA 33
- GSE280100 RNA-sequencing analysis of differential expressed genes in TGFβ-treated HK-2 cells after HDAC11 inhibition 15 samples shares hk-2, tgf
- GSE251968 Analysis of SKMEL-103, AsPC1 and RH-36 cells after treatment with BAY 11-7082 18 samples shares bay, treatment
- GSE270296 TGF-β Signaling Pathway and Cell-Cell Interactions in the Tumor Microenvironment Drive Bladder Cancer Progression after BCG Instillation Treatment: Insights from longitudinal Single-Nucleus RNA-Seq 14 samples shares tgf, treatment
- GSE255437 Analysis of A375 and SKMEL-103 cells after treatment with with DMSO as control or BAY-850 12 samples shares bay, treatment
- GSE248292 RNAseq of CONTROL engineered and SMAD4 engineered Purified NK cells after 7 day treatment in the presence/absence of TGFb 12 samples shares tgf, treatment
- GSE265848 Biological effects of recombinant S100A8, recombinant S100A9, and recombinant S100A8/S100A9 on human renal tubular epithelial cells (HK-2) 12 samples shares hk-2, tubular
- GSE293574 Effect of BAY2402234 treatment on gene expression in nasopharyngeal carcinoma C666-1 cells 10 samples shares bay, treatment
- GSE237690 Lupus dermal fibroblasts hyper-respond to inflammatory cytokines and exhibit a pro-fibrotic phenotype to TGF-β in patients with scarring skin disease 317 samples shares tgf
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.