Ubiquitin-like proteins NEDD8 and SUMO2 control epithelial homeostasis, regeneration, and inflammation
RNA-seq (gene expression) · human · 68 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
- 68 samples: 28 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.
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 GSE326753_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 PRJNA1446850 and SRA study SRP687979. Searching any of these in the dataset finder brings you back here.
Supports a case/control comparison: 6 samples read as cases, 24 as controls.
How we read this: 28 replicated groups read from 68 sample titles; they account for 62 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.
- GSM9632709 A431_DMSO_1 A431_DMSO
- GSM9632710 A431_DMSO_2 A431_DMSO
- GSM9632711 A431_NEDD8i_1 A431_NEDD8i
- GSM9632712 A431_NEDD8i_2 A431_NEDD8i
- GSM9632713 CAL27_DMSO_1 CAL27_DMSO
- GSM9632714 CAL27_DMSO_2 CAL27_DMSO
- GSM9632715 CAL27_NEDD8i_1 CAL27_NEDD8i
- GSM9632716 CAL27_NEDD8i_2 CAL27_NEDD8i
- GSM9632717 K14pos_IMQ_1 K14pos_IMQ
- GSM9632718 K14neg_IMQ_1 K14neg_IMQ
- GSM9632719 K14pos_IMQ_2 K14pos_IMQ
- GSM9632720 K14neg_DMSO_1 K14neg_DMSO
- GSM9632721 K14neg_DMSO_2 K14neg_DMSO
- GSM9632722 K14neg_DMSO_3 K14neg_DMSO
- GSM9632723 K14pos_DMSO_1 K14pos_DMSO
- GSM9632724 K14pos_DMSO_2 K14pos_DMSO
- GSM9632725 K14pos_DMSO_3 K14pos_DMSO
- GSM9632726 K14neg_IMQ_2 K14neg_IMQ
- GSM9632727 B6_IMQ_1 B6_IMQ
- GSM9632728 B6_IMQ_2 B6_IMQ
- GSM9632729 B6_DMSO_1 B6_DMSO
- GSM9632730 B6_DMSO_2 B6_DMSO
- GSM9632731 S2_K14neg_1 S2_K14neg
- GSM9632732 S2_K14neg_2 S2_K14neg
- GSM9632733 S2_K14neg_3 S2_K14neg
- GSM9632734 S2_K14pos_1 S2_K14pos
- GSM9632735 S2_K14pos_2 S2_K14pos
- GSM9632736 S2_K14pos_3 S2_K14pos
- GSM9632737 N8_K14neg_1 N8_K14neg
- GSM9632738 N8_K14neg_2 N8_K14neg
- GSM9632739 N8_K14neg_3 N8_K14neg
- GSM9632740 N8_K14pos_1 N8_K14pos
- GSM9632741 N8_K14pos_2 N8_K14pos
- GSM9632742 N8_K14pos_3 N8_K14pos
- GSM9632743 DMSO_1 DMSO
- GSM9632744 DMSO_2 DMSO
- GSM9632745 NEDD8i_1 NEDD8i
- GSM9632746 NEDD8i_2 NEDD8i
- GSM9636011 Non-recombination control skin 1 Non-recombination contr…
- GSM9636012 Sumo knockout 2 Sumo knockout
+ 28 more — browse all 68 samples with per-sample file links →
- GSE248942 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (ATAC-Seq) 123 samples shares regeneration, control
- GSE248944 Spatiotemporal control of SMARCA5 by a MAPK-RUNX1 axis distinguishes mutant KRAS-driven pancreatic malignancy from tissue regeneration (CUT&RUN) 14 samples shares regeneration, control
- GSE306977 Cell composition and gene-expression dynamics of skeletal muscle regeneration after contraction-induced injury 70 samples shares regeneration
- GSE292577 Aspiration-assisted intra-operative 3D bioprinting of scaffold-free modular units for skeletal muscle tissue regeneration 39 samples shares regeneration
- GSE227075 Pro-inflammatory macrophages impair skeletal muscle regeneration in ischemic-damaged limbs by inducing precocious differentiation of satellite cells [scRNA-seq] 22 samples shares regeneration
- GSE294342 ALDH1A1+ cells are endometrial progenitors contributing to regeneration and endometriosis 20 samples shares regeneration
- GSE261794 Interleukin-11 causes alveolar type 2 cell dysfunction and prevents alveolar regeneration 17 samples shares regeneration
- GSE303466 CD24+ human dental papilla cells as translational seed cells for dentin-pulp regeneration via BMP2/SIRT1 metabolic axis 12 samples shares regeneration
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.