stHNSCC_28

Download spatial transcriptomics data for this sample

Dataset Information

scHNDB ID

stHNSCC_28

Tissue Type

Tumor

Age

64

Gender

M

Position

Tongue

Clinical Stage

IV

Data download

Spatial transcriptomics in 10X format: MTX-style count tables plus metadata, together with a spatial/ folder for image alignment and Visium assets.

10X Raw Data Package

Download

Package contents

Barcodes

TSV.GZ

stHNSCC_28_barcodes.tsv.gz

Spot barcodes aligned to the count matrix.

Features

TSV.GZ

stHNSCC_28_features.tsv.gz

Gene IDs and feature metadata for matrix rows.

Matrix

MTX.GZ

stHNSCC_28_matrix.mtx.gz

Sparse expression matrix (genes × spots).

Metadata

CSV.GZ

stHNSCC_28_metadata.csv.gz

Per-spot annotations and sample-level fields (when provided).

Spatial folder

DIR

spatial/

Tissue positions, histology image, and scalefactors_json.json (Visium-style layout for this sample).

Usage Instructions

MTX-based Visium export: use a single folder that contains barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz, optional *_metadata.csv.gz, and a spatial/ subfolder for alignment.

In R (Seurat):

library(Seurat)
data_dir <- "path/to/extracted/folder_with_mtx_and_spatial"
counts <- Read10X(data.dir = data_dir)
obj <- CreateSeuratObject(counts = counts)

In Python (Scanpy):

import scanpy as sc
adata = sc.read_10x_mtx("path/to/extracted/folder_with_mtx_and_spatial")