Microprotein-Encoding RNA Regulation in Cells Treated with Pro-inflammatory and Pro-Fibrotic Stimuli
RNA-seq (gene expression) · human · 82 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
- 82 samples: 26 conditions, mostly in triplicateGroups 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.
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 GSE269376_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 PRJNA1121277 and SRA study SRP512463. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 82 samples.
How we read this: 26 replicated groups read from 82 sample titles; they account for 82 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.
- GSM8314000 Caco-2, differentiated, lipid micelles, rep1 Caco-2, differentiated,…
- GSM8314001 Caco-2, differentiated, lipid micelles, rep2 Caco-2, differentiated,…
- GSM8314002 Caco-2, differentiated, micelles without lipid, rep1 Caco-2, differentiated,…
- GSM8314003 Caco-2, differentiated, micelles without lipid, rep2 Caco-2, differentiated,…
- GSM8314004 Caco-2, differentiated, control, rep1 Caco-2, differentiated,…
- GSM8314005 Caco-2, differentiated, control, rep2 Caco-2, differentiated,…
- GSM8314006 Caco-2, undifferentiated, rep1 Caco-2, undifferentiate…
- GSM8314007 Caco-2, undifferentiated, rep2 Caco-2, undifferentiate…
- GSM8314008 HCEC-1CT pool1 HCEC-1CT pool
- GSM8314009 HCEC-1CT pool2 HCEC-1CT pool
- GSM8314010 CCD-18Co pool1 CCD-18Co pool
- GSM8314011 CCD-18Co pool2 CCD-18Co pool
- GSM8314012 Caco-2 pool1 Caco-2 pool
- GSM8314013 Caco-2 pool2 Caco-2 pool
- GSM8314014 PBMC pool1 PBMC pool
- GSM8314015 PBMC pool2 PBMC pool
- GSM8314016 Caco-2, differentiated, control, rep1 Caco-2, differentiated,…
- GSM8314017 Caco-2, differentiated, control, rep2 Caco-2, differentiated,…
- GSM8314018 Caco-2, differentiated, control, rep3 Caco-2, differentiated,…
- GSM8314019 Caco-2, differentiated, lipid micelles, rep1 Caco-2, differentiated,…
- GSM8314020 Caco-2, differentiated, lipid micelles, rep2 Caco-2, differentiated,…
- GSM8314021 Caco-2, differentiated, lipid micelles, rep3 Caco-2, differentiated,…
- GSM8314022 Caco-2, differentiated, micelles without lipid, rep1 Caco-2, differentiated,…
- GSM8314023 Caco-2, differentiated, micelles without lipid, rep2 Caco-2, differentiated,…
- GSM8314024 Caco-2, differentiated, micelles without lipid, rep3 Caco-2, differentiated,…
- GSM8314025 Caco-2, undifferentiated, rep1 Caco-2, undifferentiate…
- GSM8314026 Caco-2, undifferentiated, rep2 Caco-2, undifferentiate…
- GSM8314027 Caco-2, undifferentiated, rep3 Caco-2, undifferentiate…
- GSM8314050 HCEC-1CT Naive 1 HCEC-1CT Naive
- GSM8314051 HCEC-1CT Naive 2 HCEC-1CT Naive
- GSM8314052 HCEC-1CT Naive 3 HCEC-1CT Naive
- GSM8314053 HCEC-1CT 100 ng/mL LPS 1 HCEC-1CT 100 ng/mL LPS
- GSM8314054 HCEC-1CT 100 ng/mL LPS 2 HCEC-1CT 100 ng/mL LPS
- GSM8314055 HCEC-1CT 100 ng/mL LPS 3 HCEC-1CT 100 ng/mL LPS
- GSM8314056 HCEC-1CT 10 ng/mL IL-22 1 HCEC-1CT 10 ng/mL IL-22
- GSM8314057 HCEC-1CT 10 ng/mL IL-22 2 HCEC-1CT 10 ng/mL IL-22
- GSM8314058 HCEC-1CT 10 ng/mL IL-22 3 HCEC-1CT 10 ng/mL IL-22
- GSM8314059 HCEC-1CT 10 ng/mL TNFa 1 HCEC-1CT 10 ng/mL TNFa
- GSM8314060 HCEC-1CT 10 ng/mL TNFa 2 HCEC-1CT 10 ng/mL TNFa
- GSM8314061 HCEC-1CT 10 ng/mL TNFa 3 HCEC-1CT 10 ng/mL TNFa
+ 42 more — browse all 82 samples with per-sample file links →
- GSE269374 Microprotein-Encoding RNA Regulation in Cells Treated with Pro-inflammatory and Pro-Fibrotic Stimuli (RNA-Seq colon cell lines) 54 samples shares microprotein-encoding, pro-inflammatory, pro-fibrotic, treated, stimuli
- GSE298444 IgA autoantibodies trigger pro-inflammatory, pro-fibrotic and type I interferon responses in Hidradenitis suppurativa skin lesion 24 samples shares pro-inflammatory, pro-fibrotic
- GSE292059 Inflammatory Epithelial and Macrophage Pathways Underlie Residual Asthma Exacerbations in Urban Children Treated with Mepolizumab 965 samples shares treated
- GSE297164 RNA-seq profiling of radioiodine-treated differentiated thyroid cancer cells reveals DDR pathway regulation during iodine tolerance 8 samples shares treated
- GSE249009 RNA sequencing analysis of isoginkgetin and thapsigargin treated HCT116 and HCT116 ATF4 deficient cells 48 samples shares treated
- GSE281511 RNA seq of liver cancer cells treated with different concentration gradients of Thapsigargin (TG), Tunicamycin (TM), and FCCP 44 samples shares treated
- GSE242941 Transcriptional profiling of skin cancer NK cells reveals the elevated glucocorticoid receptor activity alters their pro-inflammatory features. 36 samples shares pro-inflammatory
- GSE243013 A single-cell atlas of immune heterogeneity in anti-PD1-treated non-small cell lung cancer 243 samples shares treated
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.