ZNF865 (BLST) Regulates Human Cell Senescence and DNA Damage [RNA-seq]
RNA-seq (gene expression) · human · 15 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
- 15 samples: 6 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.
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 GSE311656_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 PRJNA1370086 and SRA study SRP649356. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 6 replicated groups read from 15 sample titles; they account for 12 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.
- GSM9329036 ASC VPR NTC 1 ASC VPR NTC
- GSM9329037 ASC VPR NTC 2 ASC VPR NTC
- GSM9329038 ASC VPR ZNF865 1 ASC VPR ZNF865
- GSM9329039 ASC VPR ZNF865 2 ASC VPR ZNF865
- GSM9329040 HEK VPR NTC 1 HEK VPR NTC
- GSM9329041 HEK VPR NTC 2 HEK VPR NTC
- GSM9329042 HEK VPR ZNF865 1 HEK VPR ZNF865
- GSM9329043 HEK VPR ZNF865 2 HEK VPR ZNF865
- GSM9329044 Degenerative NP cells (32 Y M)
- GSM9329045 Healthy NP cells (69 Y F)
- GSM9329046 Healthy NP cells (32 Y F)
- GSM9329047 ZNF865 upregulated degenerative NP cells (32 Y M) 1 ZNF865 upregulated dege…
- GSM9329048 ZNF865 upregulated degenerative NP cells (32 Y M) 2 ZNF865 upregulated dege…
- GSM9329049 Degenerative NP cells (33 Y M) 1 Degenerative NP cells (…
- GSM9329050 Degenerative NP cells (33 Y M) 2 Degenerative NP cells (…
- GSE284666 SenCat: Redefining human cell senescence through multiomic profiling of multiple senescent cell types 190 samples shares senescence
- GSE327707 Sorted bulk RNA-seq profiling of human peripheral blood mononuclear cell populations across diverse in vitro immune stimuli 150 samples shares rna-seq
- GSE227835 Single-cell RNA-seq data of human PBMC from Myasthenia Gravis patients 40 samples shares rna-seq
- GSE317207 Transcriptomic profiling of human hepatocellular carcinoma biopsy samples using bulk RNA-seq 33 samples shares rna-seq
- GSE317068 Multiscale analysis and functional validation of the cellular and genetic determinants of skeletal disease [Human scRNA-seq] 32 samples shares rna-seq
- GSE310058 Single-nucleus transcriptomic profiling of human lung tissue in chronic obstructive pulmonary disease (COPD) [snRNA-seq] 149 samples shares rna-seq
- GSE298173 Circulating immune cell signature analysis in HFpEF across species [RNA-Seq - human] 18 samples shares rna-seq
- GSE342790 Development-inspired approach for the derivation of functional and transplantable salivary gland organoids from human pluripotent stem cells [RNA-Seq] 16 samples shares 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.