Effects of oxidized LDL versus IL-1ß/TNF-ɑ/INFɣ on human gingival mesenchymal stem cells properties
RNA-seq (gene expression) · human · 18 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
- 18 samples: 18 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
- Effects of oxidized LDL versus IL-1ß/TNF-ɑ/INFɣ on human gingival mesenchymal stem cells propertiesJournal of periodontal research · 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 GSE269628_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 PRJNA1122789 and SRA study SRP513286. 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 18 sample titles: 18 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.
- GSM8323165 501_Control_24h
- GSM8323166 502_Cytokine_24h
- GSM8323167 503_OxLDL_24h
- GSM8323168 504_Control_72h
- GSM8323169 505_Cytokine_72h
- GSM8323170 506_OxLDL_72h
- GSM8323171 513_Control_24h
- GSM8323172 514_Cytokine_24h
- GSM8323173 515_OxLDL_24h
- GSM8323174 516_Control_72h
- GSM8323175 517_Cytokine_72h
- GSM8323176 518_OxLDL_72h
- GSM8323177 519_Control_24h
- GSM8323178 520_Cytokine_24h
- GSM8323179 521_OxLDL_24h
- GSM8323180 522_Control_72h
- GSM8323181 523_Cytokine_72h
- GSM8323182 524_OxLDL_72h
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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.