Yoghurt consumption is associated with changes in the composition of the human gut microbiome and metabolome/Experiment 11
From BugSigDB
Needs review
Subjects
- Location of subjects
- United Kingdom
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Beverage consumption measurement Beverage consumption measurement,beverage consumption measurement
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Low Yoghurt consumers(didn't consume yoghurt 24hrs before sampling)
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- High Yoghurt consumers(didn't consume yoghurt 24hrs before sampling)
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- High Yoghurt consumers(didn't consume yoghurt 24hrs before sampling) refers to those who did not take yoghurt a day before sampling (24hours before sampling).
- Group 0 sample size Number of subjects in the control (unexposed) group
- 29
- Group 1 sample size Number of subjects in the case (exposed) group
- 34
Lab analysis
- Sequencing type
- WMS
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Illumina
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- Mixed-Effects Regression
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
- Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
- age, body mass index, sex, Confounders controlled for: "healthy eating index" is not in the list (abnormal glucose tolerance, acetaldehyde, acute graft vs. host disease, acute lymphoblastic leukemia, acute myeloid leukemia, adenoma, age, AIDS, alcohol consumption measurement, alcohol drinking, ...) of allowed values.healthy eating index
Signature 1
Needs review
Source: Fig. 2B
Description: Differential abundant taxa between low-yoghurt consumers (didn't consume yoghurt 24hrs before sampling) and high yoghurt eaters(didn't consume yoghurt 24hrs before sampling).
Abundance in Group 1: increased abundance in High Yoghurt consumers(didn't consume yoghurt 24hrs before sampling)
| NCBI | Quality Control | Links |
|---|---|---|
| Streptococcus thermophilus |
Revision editor(s): KateRasheed
