RNA-seq expression analysis of liver, adipose, skeletal muscle, heart, and pancreatic islets from DO founder strain mice fed high-fat, high-sugar diet. [liver]
RNA-seq (gene expression) · mouse · 61 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
- 61 samples: 61 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.
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 GSE266923_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 PRJNA1108726 and SRA study SRP506234. 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 61 sample titles: 61 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.
- GSM8256851 ORSAM9111_NZO_5_GT20-10638_liver
- GSM8256852 ORSAM9112_NZO_6_GT20-10605_liver
- GSM8256853 ORSAM9113_NZO_7_GT20-10577_liver
- GSM8256854 ORSAM9114_NZO_8_GT20-10603_liver
- GSM8256855 ORSAM9115_PWK_1_GT20-10630_liver
- GSM8256856 ORSAM9116_PWK_2_GT20-10560_liver
- GSM8256857 ORSAM9117_PWK_3_GT20-10553_liver
- GSM8256858 ORSAM9118_PWK_4_GT20-10582_liver
- GSM8256859 ORSAM9119_PWK_5_GT20-10637_liver
- GSM8256860 ORSAM9120_129_1_GT20-10628_liver
- GSM8256861 ORSAM9121_129_2_GT20-10607_liver
- GSM8256862 ORSAM9122_129_3_GT20-10543_liver
- GSM8256863 ORSAM9123_129_4_GT20-10526_liver
- GSM8256864 ORSAM9124_129_6_GT20-10619_liver
- GSM8256865 ORSAM9125_129_7_GT20-10555_liver
- GSM8256866 ORSAM9126_B6_1_GT20-10536_liver
- GSM8256867 ORSAM9127_B6_2_GT20-10552_liver
- GSM8256868 ORSAM9128_B6_3_GT20-10586_liver
- GSM8256869 ORSAM9129_B6_4_GT20-10596_liver
- GSM8256870 ORSAM9130_NOD_1_GT20-10622_liver
- GSM8256871 ORSAM9131_NOD_2_GT20-10539_liver
- GSM8256872 ORSAM9132_NOD_3_GT20-10640_liver
- GSM8256873 ORSAM9133_NOD_4_GT20-10564_liver
- GSM8256874 ORSAM9134_NOD_5_GT20-10569_liver
- GSM8256875 ORSAM9135_NOD_6_GT20-10599_liver
- GSM8256876 ORSAM9136_NOD_7_GT20-10581_liver
- GSM8256877 ORSAM9137_NOD_8_GT20-10547_liver
- GSM8256878 ORSAM9138_WSB_1_GT20-10589_liver
- GSM8256879 ORSAM9139_WSB_3_GT20-10583_liver
- GSM8256880 ORSAM9140_WSB_4_GT20-10625_liver
- GSM8256881 ORSAM9141_WSB_5_GT20-10643_liver
- GSM8256882 ORSAM9142_WSB_6_GT20-10611_liver
- GSM8256883 ORSAM9143_WSB_7_GT20-10612_liver
- GSM8256884 ORSAM9144_WSB_8_GT20-10617_liver
- GSM8256885 ORSAM9145_Cast_1_GT20-10537_liver
- GSM8256886 ORSAM9146_Cast_2_GT20-10634_liver
- GSM8256887 ORSAM9147_Cast_3_GT20-10608_liver
- GSM8256888 ORSAM9148_Cast_5_GT20-10627_liver
- GSM8256889 ORSAM9149_Cast_6_GT20-10527_liver
- GSM8256890 ORSAM9150_Cast_7_GT20-10613_liver
+ 21 more — browse all 61 samples with per-sample file links →
- GSE266918 RNA-seq expression analysis of liver, adipose, skeletal muscle, heart, and pancreatic islets from DO founder strain mice fed high-fat, high-sugar diet. [heart] 63 samples shares pancreatic, high-sugar, skeletal, high-fat, rna-seq, adipose, founder, muscle
- GSE266920 RNA-seq expression analysis of liver, adipose, skeletal muscle, heart, and pancreatic islets from DO founder strain mice fed high-fat, high-sugar diet. [Adipose] 61 samples shares pancreatic, high-sugar, skeletal, high-fat, rna-seq, adipose, founder, muscle
- GSE267727 Transcriptome profiling of non-islet metabolic tissues in ~500 DO mouse liver, adipose, heart, and skeletal muscle tissue from mice fed high-fat, high-sugar diet [heart] 482 samples shares high-sugar, skeletal, high-fat, adipose, muscle
- GSE253735 Loss of skeletal muscle Bmal1 +/- Exercise Training [Mouse liver, heart, inguinal white adipose and lung tissues 64 samples shares skeletal, adipose, muscle
- GSE273878 Cancer-induced FOXP1 disrupts and reprograms skeletal muscle circadian transcription in cachexia [circadian RNA-seq] 48 samples shares skeletal, rna-seq, muscle
- GSE325832 RNA-seq analysis of skeletal muscle from control (Cre) and Terf2 knockout (KO) mice in gastrocnemius-plantaris-soleus (GPS) and tibialis anterior (TA) 35 samples shares skeletal, rna-seq, muscle
- GSE267909 Single-nuclei sequencing of skeletal muscle reveals subsynaptic-specific transcripts involved in neuromuscular junction maintenance (bulk RNA-Seq) 14 samples shares skeletal, rna-seq, muscle
- GSE267910 Single-nuclei sequencing of skeletal muscle reveals subsynaptic-specific transcripts involved in neuromuscular junction maintenance (snRNA-Seq) 12 samples shares skeletal, rna-seq, muscle
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.