scHNSCC_324_MLN9

Download processed single-cell RNA-seq data for this sample

Dataset Information

scHNDB ID

scHNSCC_324_MLN9

Tissue Type

Lymph Node

Age

56

Gender

M

Position

Larynx

Clinical Stage

IV

Data download

Visium-style 10X package: filtered counts in HDF5, per-spot metadata, and a spatial/ folder with tissue alignment, high-resolution H&E, and scale factors.

10X Raw Data Package

Download

Package contents

Filtered feature matrix

H5

filtered_feature_bc_matrix.h5

Space Ranger–style filtered per-spot expression (genes × spots).

Metadata

CSV.GZ

scHNSCC_324_MLN9_metadata.csv.gz

Per-spot or sample-level annotations bundled with the package.

Tissue positions

CSV

spatial/tissue_positions_list.csv

Array coordinates linking spots to the tissue image.

H&E image (high resolution)

PNG

spatial/tissue_hires_image.png

Histology image aligned with Visium spot grid.

Scale factors

JSON

spatial/scalefactors_json.json

Pixel ↔ spot scaling and related Visium metadata.

Usage Instructions

Visium Space Ranger layout: the directory passed to the loader must contain filtered_feature_bc_matrix.h5 and a spatial/ subfolder (see 10x Visium documentation).

In R (Seurat):

library(Seurat)
data_dir <- "path/to/extracted/sample_folder"
obj <- Load10X_Spatial(data.dir = data_dir)

In Python (Scanpy):

import scanpy as sc
adata = sc.read_visium("path/to/extracted/sample_folder")