Establishment and characterization of patient-derived in-vitro and in-vivo models of penile squamous cell carcinoma
RNA-seq (gene expression) · mouse · 10 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
- 10 samples: 10 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.
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 GSE336821_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 PRJNA1483412 and SRA study SRP713387. 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 10 sample titles: 10 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.
- GSM9843369 PeCa53_patient_tissue_sample
- GSM9843370 PeCa53_primary_culture
- GSM9843371 PeCa53_xenograft_tissue_sample
- GSM9843372 PeCa60_patient_tissue_sample
- GSM9843373 PeCa60_primary_culture
- GSM9843374 PeCa60_xenograft_tissue_sample
- GSM9843375 PeCa65_patient_tissue_sample
- GSM9843376 PeCa65_primary_culture
- GSM9843377 PeCa70_patient_tissue_sample
- GSM9843378 PeCa70_primary_culture
- GSE307471 Intratumoral bacteria are immunosuppressive and promote immunotherapy resistance in head and neck squamous cell carcinoma 33 samples shares squamous
- GSE260920 Loss of DUSP1 expression creates a cold tumor microenvironment in cutaneous squamous cell carcinoma 17 samples shares squamous
- GSE281472 Targeting CD206+ macrophages disrupts the establishment of a key anti-tumor immune axis 245 samples shares establishment
- GSE333740 Human HN-SCC-151 HPV-negative head and neck squamous cell carcinoma cells treated with DMSO or the SUV420H1 inhibitor A-196/siNC (control) or siSUV420H1 siRNAs. 45 samples shares squamous
- GSE228957 Single-cell or nucleus RNAseq of neuroblastoma patient-derived xenografts 17 samples shares patient-derived
- GSE289418 Effect of the Mutated p.H222P A-type Lamins on Gene Expression in Both Patient-Derived Cardiomyocytes and Mouse Models of Dilated Cardiomyopathy 10 samples shares patient-derived
- GSE242464 Epigenetic regulation of p63 blocks squamous-to-neuroendocrine transdifferentiation in esophageal development and malignancy 53 samples shares squamous
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.