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Single-cell RNA sequencing of human iPSC-derived forebrain organoids following amyloid-β42 treatment, microglia co-culture, and maraviroc treatment

GSE339602 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2026/07/27 Platform GPL29480
At a glance

Single-cell RNA-seq · human · 16 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
16 samples: 16 samples, each with a distinct title — no replicated groupsGroups 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)
Human induced pluripotent stem cell (iPSC)-derived forebrain organoids were used to model Alzheimer's disease-associated pathology and investigate the effects of microglia co-culture and CCR5 inhibition. Day 60 forebrain organoids were assigned to four experimental groups: untreated control, amyloid-β42 (Aβ42)-treated, Aβ42-treated followed by co-culture with mature human iPSC-derived microglia, and Aβ42-treated followed by maraviroc treatment and co-culture with mature human iPSC-derived microglia.
Read the full summary ↓
Single-cell RNA sequencing was performed using the MGI DNBelab C-TaiM4 platform to characterize transcriptional changes and cellular composition across the four experimental conditions.
This dataset
Open GSE339602 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 GSE339602_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 PRJNA1499263 and SRA study SRP720472. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 12 samples read as cases, 4 as controls.

How we read this: Read from 16 sample titles: 16 distinct titles with little repetition. 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.