RNA-seq of Lgr5-GFP+ ISCs from KANSL1-deficient mice and control mice.
RNA-seq (gene expression) · mouse · 9 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Mus musculus (mouse)
- Samples
- 9 samples: 3 × Lgr5-GFP+ ISCs, KANSL1-WT, vs 3 × Lgr5-GFP+ ISCs, KANSL1-KO, day3, vs 3 × Lgr5-GFP+ ISCs, KANSL1-KO, day4,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.
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 GSE333456_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1471122 and SRA study SRP704113. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9765354 Lgr5-GFP+ ISCs, KANSL1-WT, rep1 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765355 Lgr5-GFP+ ISCs, KANSL1-WT, rep2 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765356 Lgr5-GFP+ ISCs, KANSL1-WT, rep3 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765357 Lgr5-GFP+ ISCs, KANSL1-KO, day3, rep1 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765358 Lgr5-GFP+ ISCs, KANSL1-KO, day3, rep2 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765359 Lgr5-GFP+ ISCs, KANSL1-KO, day3, rep3 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765360 Lgr5-GFP+ ISCs, KANSL1-KO, day4, rep1 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765361 Lgr5-GFP+ ISCs, KANSL1-KO, day4, rep2 Lgr5-GFP+ ISCs, KANSL1-…
- GSM9765362 Lgr5-GFP+ ISCs, KANSL1-KO, day4, rep3 Lgr5-GFP+ ISCs, KANSL1-…
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- GSE326100 scRNA-seq of mouse cochlea organoid cells 768 samples shares rna-seq
- GSE311449 Single cell RNA-seq of mouse brain vascular cells with Smart-seq2 method 391 samples shares rna-seq
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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.