Single-cell transcriptomic profiling of primary oral squamous cell carcinoma and lymph node metastatic lesions
Single-cell RNA-seq · human · 10 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)
- Topic
- Head and neck cancerThis series is part of our curated briefing on it.
- Samples
- 10 samples: 5 × PT vs 5 × METGroups 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 GSE322620_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 PRJNA1430742 and SRA study SRP680326. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 10 samples.
How we read this: 2 replicated groups read from 10 sample titles; they account for 10 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.
- GSM9555766 PT1 PT
- GSM9555767 PT2 PT
- GSM9555768 PT3 PT
- GSM9555769 PT4 PT
- GSM9555770 PT5 PT
- GSM9555771 MET1 MET
- GSM9555772 MET2 MET
- GSM9555773 MET3 MET
- GSM9555774 MET4 MET
- GSM9555775 MET5 MET
- GSE140042 Single-cell atlas of head and neck squamous cell carcinoma 18 samples same disease briefing · shares single-cell, squamous
- GSE173647 Single-cell Sequencing Analysis of Head and Neck Squamous Cell Carcinoma 2 samples same disease briefing · shares single-cell, squamous
- GSE176077 RNA-seq profiling of salivary transcriptome reveals potential diagnostic RNAs and oral microbial dysbiosis in oral squamous cell carcinoma 28 samples same disease briefing · shares squamous, oral
- GSE164690 Investigating Immune and Non-Immune Cell Interactions in Head and Neck Tumors by Single-Cell RNA Sequencing 51 samples same disease briefing · shares single-cell
- GSE181919 Single-cell transcriptome profiling of the stepwise progression of head and neck cancer 37 samples same disease briefing · shares single-cell
- GSE114446 Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines 33 samples same disease briefing · shares single-cell
- GSE185965 Single cell RNA sequencing of head and neck squamous carcinoma (HNSCC) patient sample 3 samples same disease briefing · shares squamous
- GSE103322 Single cell RNA-seq analysis of head and neck cancer 5901 samples same disease briefing
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.