Investigation of EMT Processes in Migrating Mammary Epithelial Organoids
RNA-seq (gene expression) · mouse · 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
- Mus musculus (mouse)
- Samples
- 15 samples: 5 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 GSE296474_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 PRJNA1259450 and SRA study SRP583357. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 14 samples.
How we read this: 5 replicated groups read from 15 sample titles; they account for 14 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.
- GSM8970987 0h-1 0h
- GSM8970988 0h-2 0h
- GSM8970989 0h-4 0h
- GSM8970990 BSA-36h-1 BSA-36h
- GSM8970991 BSA-36h-2 BSA-36h
- GSM8970992 BSA-36h-3 BSA-36h
- GSM8970993 BSA-72h-2_1 BSA-72h-2
- GSM8970994 BSA-72h-2_2 BSA-72h-2
- GSM8970995 BSA-72h-3
- GSM8970996 FGF0-72h-2 FGF0-72h
- GSM8970997 FGF0-72h-3 FGF0-72h
- GSM8970998 FGF0-72h-4 FGF0-72h
- GSM8970999 FGF10-36h-1 FGF10-36h
- GSM8971000 FGF10-36h-3 FGF10-36h
- GSM8971001 FGF10-36h-4 FGF10-36h
- GSE253461 Single-cell transcriptional profiling of wildtype Rosa26(YFP) (Y) and Kras(G12D) p53(-/-) Rosa26-YFP (KPY) lung AT2 epithelial cells, AT2 organoids, and co-cultured mesenchymal cells with temporal resolution 39 samples shares epithelial, organoids
- GSE269973 Signaling basis of gastric epithelial cell differentiation revealed by human and mouse organoids [RNA-Seq] 32 samples shares epithelial, organoids
- GSE240698 Thymic epithelial organoids mediate T cell development 11 samples shares epithelial, organoids
- GSE279627 Mammary intraepithelial lymphocytes promote lactogenesis and offspring fitness 24 samples shares epithelial, mammary
- GSE198337 Epigenomic disorder and partial EMT impair luminal progenitor integrity in Brca1-associated breast tumorigenesis 11 samples shares emt
- GSE87472 The EMT-activator Zeb1 is crucial for cellular plasticity and drives metastasis in pancreatic cancer 36 samples shares emt
- GSE274984 Gene expression profiling of corneal and limbal epithelial cells in young and aged mice 378 samples shares epithelial
- GSE166225 Inference of emergent spatio-temporal processes from single-cell sequencing reveals feedback between de novo DNA methylation and chromatin condensates [RNA-seq] 288 samples shares processes
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.