Detecting Circadian Rhythmicity By Single Cell Multiomics
Single-cell RNA-seq · mouse · 12 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 12 samples: 12 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.
- Paper
- Single-Cell Multiomic Analysis of Circadian Rhythmicity in Mouse LiverbioRxiv : the preprint server for biology · 2025
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 GSE288579_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 PRJNA1218624 and SRA study SRP561216. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 12 sample titles: 12 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.
- GSM8770198 WT1 scRNA-seq
- GSM8770199 WT2 scRNA-seq
- GSM8770200 WT3 scRNA-seq
- GSM8770201 WT4 scRNA-seq
- GSM8770202 WT5 scRNA-seq
- GSM8770203 WT6 scRNA-seq
- GSM8770204 WT1 scATAC-seq
- GSM8770205 WT2 scATAC-seq
- GSM8770206 WT3 scATAC-seq
- GSM8770207 WT4 scATAC-seq
- GSM8770208 WT5 scATAC-seq
- GSM8770209 WT6 scATAC-seq
- GSE198409 Dual Role of PRC2-EZH1 in Orchestrating Rhythmicity of Circadian Transcriptional Program in Post-mitotic Skeletal Muscle Cells 78 samples shares rhythmicity, circadian
- GSE240483 NAD+ controls circadian rhythmicity during cardiac aging 30 samples shares rhythmicity, circadian
- GSE39860 Transcriptional Architecture and Chromatin Landscape of the Core Circadian Clock in Mammals 150 samples shares circadian
- GSE261698 A glial circadian gene expression atlas reveals cell type and disease-specific reprogramming in response to amyloid pathology or aging 165 samples shares circadian
- GSE54652 A circadian gene expression atlas in mammals: Implications for biology and medicine 384 samples shares circadian
- GSE54650 A circadian gene expression atlas in mammals assayed by microarray 288 samples shares circadian
- GSE297702 Light and sex modify Snord116 genotype effects on metabolism, behavior, and imprinted gene networks following circadian entrainment 219 samples shares circadian
- GSE287141 RNA Polymerase II Transcriptional Pausing and Release Regulates Circadian Transcription 219 samples shares circadian
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.