Gut Microbiota Orchestrates Energy Homeostasis during Cold
RNA-seq (gene expression) · mouse · 60 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
- 60 samples: 52 distinct titles, 4 of them repeatedGroups 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 GSE74228_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 PRJNA299602 and SRA study SRP065234. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 60 sample titles: 52 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.
- GSM1912430 RT1
- GSM1912431 RT2
- GSM1912432 RT3
- GSM1912433 CT1
- GSM1912434 CT2
- GSM1912435 CT3
- GSM1912436 RAB1
- GSM1912437 RAB2
- GSM1912438 RAB3
- GSM1912439 CAB1
- GSM1912440 CAB2
- GSM1912441 CAB3
- GSM1914920 day0 RT1 feces
- GSM1914921 day0 RT2 feces
- GSM1914922 day0 RT3 feces
- GSM1914923 day0 RT4 feces
- GSM1914924 day0 RT5 feces
- GSM1914925 day0 RT6 feces
- GSM1914926 day0 Cold1 feces
- GSM1914927 day0 Cold2 feces
- GSM1914928 day0 Cold3 feces
- GSM1914929 day0 Cold4 feces
- GSM1914930 day0 Cold5 feces
- GSM1914931 day0 Cold6 feces
- GSM1914932 day0 Cold7 feces
- GSM1914933 day11 RT1 feces
- GSM1914934 day11 RT2 feces
- GSM1914935 day11 RT3 feces
- GSM1914936 day11 RT5 feces
- GSM1914937 day11 RT6 feces
- GSM1914938 day11 Cold1 feces
- GSM1914939 day11 Cold2 feces
- GSM1914940 day11 Cold3 feces
- GSM1914941 day11 Cold4 feces
- GSM1914942 day11 Cold6 feces
- GSM1914943 day11 Cold7 feces
- GSM1914944 day11 Cold8 feces
- GSM1914945 day31 RT1 feces
- GSM1914946 day31 RT2 feces
- GSM1914947 day31 RT3 feces
+ 20 more — browse all 60 samples with per-sample file links →
- GSE100339 The intestinal microbiota regulates body composition through NFIL3 and the circadian clock 32 samples shares microbiota
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.