KANSL3 directs transcriptional programs essential for hepatic metabolism and differentiation [scRNA-seq]
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: 4 × scRNAseq, neonatal liver, WT, vs 4 × scRNAseq, neonatal liver, Kansl3 LKO, vs 2 × scRNAseq, old liver, Kansl3 LKO, vs 2 × scRNAseq, old liver, WT,Groups 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
- KANSL3 directs transcriptional programs essential for hepatic metabolism and differentiationLife science alliance · 2025
Read the full summary ↓
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 GSE277833_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 PRJNA1164293 and SRA study SRP534257. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 12 samples.
How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.
- GSM8532402 scRNAseq, neonatal liver, WT, rep1 scRNAseq, neonatal live…
- GSM8532403 scRNAseq, neonatal liver, WT, rep2 scRNAseq, neonatal live…
- GSM8532404 scRNAseq, neonatal liver, WT, rep3 scRNAseq, neonatal live…
- GSM8532405 scRNAseq, neonatal liver, WT, rep4 scRNAseq, neonatal live…
- GSM8532406 scRNAseq, neonatal liver, Kansl3 LKO, rep1 scRNAseq, neonatal live…
- GSM8532407 scRNAseq, neonatal liver, Kansl3 LKO, rep2 scRNAseq, neonatal live…
- GSM8532408 scRNAseq, neonatal liver, Kansl3 LKO, rep3 scRNAseq, neonatal live…
- GSM8532409 scRNAseq, neonatal liver, Kansl3 LKO, rep4 scRNAseq, neonatal live…
- GSM8532410 scRNAseq, old liver, Kansl3 LKO, rep1 scRNAseq, old liver, Ka…
- GSM8532411 scRNAseq, old liver, Kansl3 LKO, rep2 scRNAseq, old liver, Ka…
- GSM8532412 scRNAseq, old liver, WT, rep1 scRNAseq, old liver, WT,
- GSM8532413 scRNAseq, old liver, WT, rep2 scRNAseq, old liver, WT,
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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.