← BioTransfer GEO Dataset Finder
GEO series

Spatiotemporal transcriptional atlas of lung adenocarcinoma from adenocarcinoma in situ to invasive carcinoma [scRNA-seq]

GSE189357 Homo sapiens (human) Single-cell RNA-seq 9 samples Submitted 2021/11/30 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 9 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
Lung cancerThis series is part of our curated briefing on it.
Samples
9 samples
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.
Summary (written by the submitters)
To illuminate the evolutionary trajectory of LUAD from AIS to IAC, high-throughput scRNA-seq and ST data were generated and integrated to create a large-scale, single-cell spatiotemporal atlas of LUAD. We compiled a multi-omics atlas of the early-stage LUAD invasion process that reflects the heterogeneity of cancer cells, the competitive polyclonal origin of LUAD, signalling interactions between cancer cells and the TME, and the pseudo-chronological nature of LUAD invasion.
Read the full summary ↓
The spatial distribution characteristics of LUAD cells revealed the spatial heterogeneity of LUAD and the mechanism of spatial immune escape in LUAD, which provides strong evidence supporting clinical diagnosis and surgical intervention at the single-cell level.
This dataset
Download · which file do I need?

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.

1 · Just have a look

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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE189357_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

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 PRJNA782639 and SRA study SRP347260. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 9 more — browse all 9 samples with per-sample file links →

More Lung cancer datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.