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Increased hepatoprotective effects of the novel farnesoid X receptor agonist INT-787 versus obeticholic acid in a mouse model of nonalcoholic steatohepatitis

GSE263273 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2024/04/11 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 28 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
28 samples: 10 × Liver, Vehicle, vs 9 × Liver, OCA 30 mg/kg, vs 9 × Liver, INT-787 30 mg/kg,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
Increased hepatoprotective effects of the novel farnesoid X receptor agonist INT-787 versus obeticholic acid in a mouse model of nonalcoholic steatohepatitisPloS one · 2024
Summary (written by the submitters)
We applied RNA sequencing to study the hepatic gene expression profile of Lep(ob/ob) mice fed the Amylin liver NASH (AMLN) diet for 14 weeks and then treated for 2 weeks with vehicle (n=10), obeticholic acid (OCA) (n=9), or INT-787 (n=9). INT-787, which is equipotent to OCA but more hydrophilic, modulated a substantially greater number of genes associated with FXR signaling, lipid metabolism, and stellate cell activation relative to OCA.
Published in
Increased hepatoprotective effects of the novel farnesoid X receptor agonist INT-787 versus obeticholic acid in a mouse model of nonalcoholic steatohepatitis
Adorini L, Rigbolt K, Feigh M et al. · PloS one 2024 · PMID 38662778 · doi:10.1371/journal.pone.0300809
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 GSE263273_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 PRJNA1096425 and SRA study SRP499857. Searching any of these in the dataset finder brings you back here.

Study design
10 × Liver, Vehicle, vs 9 × Liver, OCA 30 mg/kg, vs 9 × Liver, INT-787 30 mg/kg,

Supports a between-group comparison across 28 samples.

How we read this: 3 replicated groups read from 28 sample titles; they account for 28 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.

Samples in this study
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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.