Gene expression profile at single cell level of human melanoma cell lines, normal human melanocytes and human nevus cells.
Single-cell RNA-seq · human · 2 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Homo sapiens (human)
- Samples
- 2 samples: 2 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
- A BRN2:MYC transcriptional axis regulates interconversion between therapy-resistant and tumorigenic phenotypes in melanomaCell reports · 2025
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 GSE230574_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA961787 and SRA study SRP434941. 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 2 sample titles: 2 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.
- GSM7226899 19145X1 Nevus
- GSM7226900 19145X2 Cultured melanomas and melanocytes
- GSE290927 Gene expression profile at single cell level of human laryngeal normal, preneoplastic and tumorigenic states 40 samples shares normal, level
- GSE269936 Gene expression profile at single cell level for human metastatic melanoma samples 38 samples shares melanoma, level
- GSE288221 RNA sequencing human melanoma, glioblastoma and pancreatic adenocarcinoma cell lines 32 samples shares melanoma, lines
- GSE252347 RNA-Seq of human cutaneous squamous cell carcinoma cell lines and normal human epidermal keratinocytes. 12 samples shares normal, lines
- GSE329231 Epigenomic profiling of H3K9me3 and H3K27ac across melanoma cell lines with different mutational backgrounds 45 samples shares melanoma, lines
- GSE254569 Gene expression profiles at single-cell level of human post-mortem brain tissue from the orbitofrontal cortex 92 samples shares level
- GSE264503 Gene expression profile of clinical ESCC tumors, matched normal tissue and lymph node metastatic tissue by RNA-seq analysis 51 samples shares normal
- GSE294300 Single-cell gene expression profiles of cells from primary colorectal cancer and adjacent normal tissue [scRNA-Seq] 36 samples shares normal
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.