GEO series

Leveraging Single-Cell Sequencing to Classify and Characterize Tumor Subgroups in Bulk RNA-Sequencing Data

GSE264680 Homo sapiens (human) Single-cell RNA-seq 167 samples Submitted 2024/04/23 Platform GPL20301

At a glance

Single-cell RNA-seq · human · 167 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: 167 samples: 9 conditions, mostly with about 4 replicates eachGroups 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.

Summary (written by the submitters)

We develop an algorithm for the integration of single-cell sequencing, RNA-inferred CNVs, and bulk transcriptomic sequencing to improve molecular classification of tumor sub-groups.

This dataset

Open GSE264680 in finder → Find more human RNA-seq datasets →

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.

Series matrix ↓

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 GSE264680_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓

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.

Raw reads on ENA ↗

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 PRJNA1103795 and SRA study SRP503660. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly with about 4 replicates each

21-01 ×56 19-01 ×38 20-01 ×30 22-01 ×25 16-01 ×4 17-01 ×4 15-01 ×3 18-01 ×3 +3 more

Supports a between-group comparison across 165 samples.

How we read this: 9 replicated groups read from 167 sample titles; they account for 165 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.

Samples in this study

GSM8225433 11-01-004
GSM8225434 13-01-003
GSM8225435 15-01-037 15-01
GSM8225436 15-01-040 15-01
GSM8225437 15-01-041 15-01
GSM8225438 16-01-004 16-01
GSM8225439 16-01-026 16-01
GSM8225440 16-01-027 16-01
GSM8225441 16-01-031 16-01
GSM8225442 17-01-027 17-01
GSM8225443 17-01-037 17-01
GSM8225444 17-01-038 17-01
GSM8225445 17-01-041 17-01
GSM8225446 18-01-010 18-01
GSM8225447 18-01-016 18-01
GSM8225448 18-01-054 18-01
GSM8225449 19-01-003 19-01
GSM8225450 19-01-005 19-01
GSM8225451 19-01-007 19-01
GSM8225452 19-01-008 19-01
GSM8225453 19-01-016 19-01
GSM8225454 19-01-017 19-01
GSM8225455 19-01-018 19-01
GSM8225456 19-01-023 19-01
GSM8225457 19-01-026 19-01
GSM8225458 19-01-027 19-01
GSM8225459 19-01-029 19-01
GSM8225460 19-01-030 19-01
GSM8225461 19-01-032 19-01
GSM8225462 19-01-038 19-01
GSM8225463 19-01-047 19-01
GSM8225464 19-01-049 19-01
GSM8225465 19-01-051 19-01
GSM8225466 19-01-054 19-01
GSM8225467 19-01-055 19-01
GSM8225468 19-01-057 19-01
GSM8225469 19-01-061 19-01
GSM8225470 19-01-063 19-01
GSM8225471 19-01-064 19-01
GSM8225472 19-01-072 19-01

+ 127 more — browse all 167 samples with per-sample file links →

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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.