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Social Processing in the Amygdala: Single-Nucleus RNA-Sequencing Reveals Distinct Neuronal Responses to Dominant and Subordinate Cues

GSE310656 Mus musculus (mouse) Single-nucleus RNA-seq 2 samples Submitted 2026/02/18 Platform GPL24247
At a glance

Single-nucleus RNA-seq · mouse · 2 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism
Mus musculus (mouse)
Samples
2 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.
Paper
Social Processing in the Amygdala: Single-Nucleus RNA-Sequencing Reveals Distinct Neuronal Responses to Dominant and Subordinate CuesbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Single-nucleus RNA-sequencing (snRNA-seq) was performed on mouse amygdala tissue to examine transcriptional responses to social olfactory cues associated with dominant and subordinate individuals. nuclei were isolated from the amygdala and processed using the 10x Genomics 3’ platform. The resulting dataset includes cell-type annotations and differential expression profiles across conditions. These data support investigation of neuronal population structure and gene expression changes underlying social cue processing.
Published in
Social Processing in the Amygdala: Single-Nucleus RNA-Sequencing Reveals Distinct Neuronal Responses to Dominant and Subordinate Cues
Dwortz MF, Hofmann HA, Curley JP · bioRxiv : the preprint server for biology 2025 · PMID 41394672 · doi:10.1101/2025.11.24.690183
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 GSE310656_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 PRJNA1366830 and SRA study SRP647163. Searching any of these in the dataset finder brings you back here.

Samples in this study

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