The intestinal clock controls host’s metabolic response to diet by driving intestinal metabolic functions and the fiber-dependent microbiome
RNA-seq (gene expression) · mouse · 48 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
- 48 samples: 48 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 GSE229963_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 PRJNA956901 and SRA study SRP433195. 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 48 sample titles: 48 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.
- GSM7181968 SV384_JE_KO_CT1
- GSM7181969 SV401_JE_WT_CT9
- GSM7181970 SV385_JE_KO_CT1
- GSM7181971 SV402_JE_KO_CT9
- GSM7181972 SV395_JE_KO_CT13
- GSM7181973 SV410_JE_KO_CT9
- GSM7181974 SV396_JE_WT_CT13
- GSM7181975 SV412_JE_WT_CT9
- GSM7181976 SV397_JE_WT_CT13
- GSM7181977 SV415_JE_WT_CT9
- GSM7181978 SV398_JE_WT_CT17
- GSM7181979 SV416_JE_KO_CT17
- GSM7181980 SV399_JE_KO_CT17
- GSM7181981 SV417_JE_WT_CT17
- GSM7181982 SV400_JE_KO_CT9
- GSM7181983 SV418_JE_KO_CT9
- GSM7181984 SV420_JE_WT_CT9
- GSM7181985 SV434_JE_WT_CT21
- GSM7181986 SV440_JE_KO_CT5
- GSM7181987 SV444_JE_KO_CT21
- GSM7181988 SV448_JE_KO_CT13
- GSM7181989 SV454_JE_WT_CT1
- GSM7181990 SV470_JE_KO_CT21
- GSM7181991 SV478_JE_KO_CT5
- GSM7181992 SV421_JE_WT_CT13
- GSM7181993 SV437_JE_KO_CT17
- GSM7181994 SV441_JE_WT_CT21
- GSM7181995 SV445_JE_KO_CT21
- GSM7181996 SV449_JE_KO_CT13
- GSM7181997 SV455_JE_WT_CT1
- GSM7181998 SV471_JE_KO_CT21
- GSM7181999 SV479_JE_KO_CT1
- GSM7182000 SV424_JE_WT_CT13
- GSM7182001 SV438_JE_WT_CT17
- GSM7182002 SV442_JE_WT_CT5
- GSM7182003 SV446_JE_WT_CT5
- GSM7182004 SV450_JE_KO_CT13
- GSM7182005 SV468_JE_WT_CT1
- GSM7182006 SV476_JE_WT_CT21
- GSM7182007 SV480_JE_KO_CT1
+ 8 more — browse all 48 samples with per-sample file links →
- GSE262065 A small intestinal bile acid modulates the gut microbiome to improve host metabolic phenotypes following bariatric surgery 10 samples shares intestinal, microbiome, host
- GSE278548 Metabolic modeling reveals the aging-associated decline of host-microbiome metabolic interactions in mice 119 samples shares microbiome, host
- GSE293180 Analysis of Host and Microbiome Responses to Antibiotics Reveals Microbiota-Independent Effects on Gut Immune Response [multiabx] 97 samples shares microbiome, host
- GSE275418 Weaning-Driven Gut Microbiome Shapes Intestinal Stem Cell Epigenetics to Train Immunological Memory (RNA-seq) 18 samples shares intestinal, microbiome
- GSE278384 Colonic Epithelial-derived FGF1 Protects against Inflammatory Bowel Disease via Driving Intestinal Stem Cells Differentiation toward Goblet Cells 12 samples shares intestinal, driving
- GSE311539 Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (Bulk-RNAseq) 10 samples shares microbiome, controls
- GSE293364 Analysis of Host and Microbiome Responses to Antibiotics Reveals Microbiota-Independent Effects on Gut Immune Response. 101 samples shares microbiome, host
- GSE228457 IL-7 mediated immunoregulatory feedback loop promotes dampening of immune effector functions by hypoinflammatory monocytes. 305 samples shares functions
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.