TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degeneration
Single-cell RNA-seq · human · 54 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Homo sapiens (human)
- Samples
- 54 samples: 22 conditions, mostly in duplicateGroups 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.
- Paper
- TGF-β signaling promotes astroglial activation and TDP-43 proteinopathy in organoid models of frontotemporal lobar degenerationThe Journal of clinical investigation · 2026
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE282668_RAW.tar (it can run to tens of gigabytes).
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 PRJNA1189572 and SRA study SRP547070. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 52 samples.
How we read this: 22 replicated groups read from 54 sample titles; they account for 52 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.
- GSM8648592 B1-CX-KO-5w-r1 B1-CX-KO-5w
- GSM8648593 B1-CX-KO-5w-r2 B1-CX-KO-5w
- GSM8648594 B1-CX-KO-16w-o1 B1-CX-KO-16w-o
- GSM8648595 B1-CX-KO-16w-o2 B1-CX-KO-16w-o
- GSM8648596 B1-CX-KO-25w-o1 B1-CX-KO-25w-o
- GSM8648597 B1-CX-KO-25w-o2 B1-CX-KO-25w-o
- GSM8648598 B1-CX-WT-5w-r1 B1-CX-WT-5w
- GSM8648599 B1-CX-WT-5w-r2 B1-CX-WT-5w
- GSM8648600 B1-CX-WT-5w-r3 B1-CX-WT-5w
- GSM8648601 B1-CX-WT-5w-r4 B1-CX-WT-5w
- GSM8648602 B1-CX-WT-16w-o1 B1-CX-WT-16w-o
- GSM8648603 B1-CX-WT-16w-o2 B1-CX-WT-16w-o
- GSM8648604 B1-CX-WT-16w-o3 B1-CX-WT-16w-o
- GSM8648605 B1-CX-WT-25w-o1 B1-CX-WT-25w-o
- GSM8648606 B1-CX-WT-25w-o2 B1-CX-WT-25w-o
- GSM8648607 B1-CX-WT-25w-o3 B1-CX-WT-25w-o
- GSM8648608 B1-CX-WT-25w-o4 B1-CX-WT-25w-o
- GSM8648609 B2-CX-KO-5w-r1 B2-CX-KO-5w
- GSM8648610 B2-CX-KO-5w-r2 B2-CX-KO-5w
- GSM8648611 B2-CX-KO-16w-o1 B2-CX-KO-16w-o
- GSM8648612 B2-CX-KO-16w-o2 B2-CX-KO-16w-o
- GSM8648613 B2-CX-KO-16w-o3 B2-CX-KO-16w-o
- GSM8648614 B2-CX-KO-25w-o1 B2-CX-KO-25w-o
- GSM8648615 B2-CX-KO-25w-o2 B2-CX-KO-25w-o
- GSM8648616 B2-CX-KO-25w-o3 B2-CX-KO-25w-o
- GSM8648617 B2-CX-KO-25w-o4 B2-CX-KO-25w-o
- GSM8648618 B2-CX-WT-5w-r1 B2-CX-WT-5w
- GSM8648619 B2-CX-WT-5w-r2 B2-CX-WT-5w
- GSM8648620 B2-CX-WT-16w-o1
- GSM8648621 B2-CX-WT-25w-o1 B2-CX-WT-25w-o
- GSM8648622 B2-CX-WT-25w-o2 B2-CX-WT-25w-o
- GSM9518218 B1-KOLF21-5w-r1 B1-KOLF21-5w
- GSM9518219 B1-KOLF21-5w-r2 B1-KOLF21-5w
- GSM9518220 B1-KOLF21-16w-o1 B1-KOLF21-16w-o
- GSM9518221 B1-KOLF21-16w-o2 B1-KOLF21-16w-o
- GSM9518222 B1-KOLF21-25w-o1 B1-KOLF21-25w-o
- GSM9518223 B1-KOLF21-25w-o2 B1-KOLF21-25w-o
- GSM9518224 B1-R493X-5w-r2
- GSM9518225 B1-R493X-16w-o1 B1-R493X-16w-o
- GSM9518226 B1-R493X-16w-o2 B1-R493X-16w-o
+ 14 more — browse all 54 samples with per-sample file links →
- GSE104193 Hypoxia-mediated translational activation of ITGB3 in breast cancer cells enhances TGF-β signalling and malignant features in vitro and in vivo 32 samples shares tgf, activation
- GSE320556 TGF-beta promotes human T follicular helper cell stemness properties at the expense of effector function 12 samples shares tgf, promotes
- GSE240485 TGF-β-induced MIR99AHG synergizes with PTBP1 to trigger an alternative splicing switch of SMARCA1 that promotes invadopodia formation for metastasis in colorectal cancer 12 samples shares tgf, promotes
- GSE300358 TGFβ signaling promotes cell cycle progression and resistance to the CDK4/6 inhibitor palbociclib through SOX4 transcriptional modulation in breast cancer cells 40 samples shares tgf, promotes
- GSE298758 DCPS modulates TDP-43 mediated neurodegeneration through P-body regulation [RNA-seq] 36 samples shares tdp-43, degeneration
- GSE316327 HP1α depletion and TGFβ activation exert antagonistic effects on 3D genome organization 18 samples shares tgf, activation
- GSE288106 Alterations in single-cell transcriptomic levels and cellular localisation of hnRNP proteins in Frontotemporal Lobar Degeneration 16 samples shares frontotemporal, degeneration
- GSE237690 Lupus dermal fibroblasts hyper-respond to inflammatory cytokines and exhibit a pro-fibrotic phenotype to TGF-β in patients with scarring skin disease 317 samples shares tgf
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.