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Identification of a hepatocyte stem cell and its niche in liver homeostasis

GSE68806 Mus musculus (mouse) RNA-seq (gene expression) 6 samples Submitted 2015/08/07 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 6 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
6 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.
Summary (written by the submitters)
Summary: RNAseq analysis of Axin2+ hepatocyte stem cells versus Axin2- mature hepatocytes shows that Axin2+ cells have a distinct gene expression profile compared to Axin2- hepatocytes. Methods: Hepatocytes were isolated from 8 week old Axin2rtTA;TetO-H2B-GFP mice (n = 3) given doxycycline in drinking water for 7 days. After removal of non-parenchymal cells, the hepatocytes were sorted into GFP+ versus GFP- populations by FACS.
Read the full summary ↓
mRNA was isolated and RNAseq profiles were generated using Illumina HiSeq 2000. The reads were mapped to the mouse genome (mm10) using TopHat (v2.0.11) and differential gene expression analysis was performed using CuffDiff (v.2.2.2). Results: We mapped about 60 million sequence reads per sample to the mouse genome (build mm10) and identified more than 30,000 transcripts in the Axin2+ and Axin2- cell populations. Differential gene expression analysis using CuffDiff identified 96 genes with signficantly different expression levels between the two populations. Several of these were confirmed by RNA in situ and qRT-PCR analysis.
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 GSE68806_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: 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 PRJNA283831 and SRA study SRP058250. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 6 more — browse all 6 samples with per-sample file links →

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