5G-exposed human skin cells do not respond with altered gene expression and methylation profiles [RNA-Seq]
DNA methylation · human · 120 samples
- What it is
- DNA methylationChemical marks on DNA that help switch genes on or off.
- Organism
- Homo sapiens (human)
- Samples
- 120 samples: 120 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.
- Paper
- 5G-exposed human skin cells do not respond with altered gene expression and methylation profilesPNAS nexus · 2025
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 GSE271704_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 beta-value tables or raw IDAT files among the supplementary files.
Also filed as BioProject PRJNA1132959 and SRA study SRP518496. 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 120 sample titles: 120 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.
- GSM8382919 Exp-V1K_2A,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-sham
- GSM8382920 Exp-V1K_2B,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-exposed
- GSM8382921 Exp-V1K_3A,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-sham
- GSM8382922 Exp-V1K_3B,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-exposed
- GSM8382923 Exp-V1K_4A,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-exposed
- GSM8382924 Exp-V1K_4B,Cell-HaCaT,Power-1,Frequency-27,Time-48,Treatment-sham
- GSM8382925 Exp-V2K_4A,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382926 Exp-V2K_4B,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382927 Exp-V2K_5A,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382928 Exp-V2K_5B,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382929 Exp-V2K_6A,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382930 Exp-V2K_6B,Cell-HaCaT,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382931 Exp-V3K_1A,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382932 Exp-V3K_1B,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382933 Exp-V3K_3A,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382934 Exp-V3K_3B,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382935 Exp-V3K_4A,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382936 Exp-V3K_4B,Cell-HaCaT,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382937 Exp-V4K_1A,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-exposed
- GSM8382938 Exp-V4K_1B,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-sham
- GSM8382939 Exp-V4K_3A,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-exposed
- GSM8382940 Exp-V4K_3B,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-sham
- GSM8382941 Exp-V4K_4A,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-sham
- GSM8382942 Exp-V4K_4B,Cell-HaCaT,Power-1,Frequency-40.5,Time-48,Treatment-exposed
- GSM8382943 Exp-V2H_1A,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382944 Exp-V2H_1B,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382945 Exp-V2F_2A,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382946 Exp-V2F_2B,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382947 Exp-V2F_3A,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-sham
- GSM8382948 Exp-V2F_3B,Cell-HDF,Power-1,Frequency-40.5,Time-2,Treatment-exposed
- GSM8382949 Exp-V3F_1A,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382950 Exp-V3F_1B,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382951 Exp-V3F_2A,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382952 Exp-V3F_2B,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382953 Exp-V3F_3A,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-exposed
- GSM8382954 Exp-V3F_3B,Cell-HDF,Power-1,Frequency-27,Time-2,Treatment-sham
- GSM8382955 Exp-V1F_2A,Cell-HDF,Power-1,Frequency-40.5,Time-48,Treatment-exposed
- GSM8382956 Exp-V1F_2B,Cell-HDF,Power-1,Frequency-40.5,Time-48,Treatment-sham
- GSM8382957 Exp-V1F_3A,Cell-HDF,Power-1,Frequency-40.5,Time-48,Treatment-exposed
- GSM8382958 Exp-V1F_3B,Cell-HDF,Power-1,Frequency-40.5,Time-48,Treatment-sham
+ 80 more — browse all 120 samples with per-sample file links →
- GSE292130 Longitudinal changes in DNA methylation in IDH-mutant glioma fuel disease progression through altered cell state differentiation [scRNA-seq] 31 samples shares methylation, altered, rna-seq
- GSE330762 Kabuki syndrome type I fibroblast multi-omics dataset: bulk RNA-seq profiles from primary skin fibroblasts 19 samples shares profiles, rna-seq, skin
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares profiles, rna-seq
- GSE271408 Single-cell RNA-sequencing identifies unique cell-specific gene expression profiles in high-grade cardiac allograft vasculopathy 16 samples shares profiles, rna-seq
- GSE261012 Single-cell gene expression profiles of cells from colorectal cancer and chemically induced PDOs [scRNA-Seq] 12 samples shares profiles, rna-seq
- GSE274999 Clinical response to azacitidine in MDS is associated with distinct DNA methylation changes in HSPCs [RNA-Seq] 52 samples shares methylation, rna-seq
- GSE253557 Single-nuclei RNA-Seq profiles from Group 3 and Group 4 medulloblastomas [scRNA-Seq] 39 samples shares profiles, rna-seq
- GSE274217 METTL3-dependent m6A RNA methylation represses transposable elements derived enhancers to suppress naïve pluripotency in human pluripotent stem cells [RNA-Seq] 28 samples shares methylation, 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.