Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Ena-DATASET-KULVIB-08-03-2016-08:57:05:036-91 - samples

ABSTRACT: Here, we studied well-phenotyped individuals from the Flemish Gut Flora Project (FGFP, N=1,106, Belgium) and the effect of environments on microbiome. The 69 major significant phenotypes found in this study are provided.

PROVIDER: EGAD00001001943 | EGA |

REPOSITORIES: EGA

ACCESS DATA

Json Xml

Similar Datasets

Flemish Gut Flora Project

Project description:"Here, we studied well-phenotyped individuals from the Flemish Gut Flora Project (FGFP, N=1,106, Belgium) and the effect of environments on microbiome."

| EGAS00001001689 | EGA

ena-DATASET-KULVIB-13-05-2020-09:14:12:689-434 - samples

Project description:16S sequencing data from 2259 Flemish Gut Flora Project (FGFP) samples

| EGAD00001006141 | EGA

ena-DATASET-KULVIB-09-11-2018-09:27:51:686-23 - samples

Project description:16S sequencing data (dual-index) from 1054 Flemish Gut Flora Project (FGFP) samples

| EGAD00001004449 | EGA

ena-DATASET-KULVIB-12-11-2018-21:44:55:968-89 - samples

Project description:FGFP (Flemish Gut Flora Project, N=100) and TR-MDD (Treatment-Resistant Major Depression Disorder, N=7) shotgun sequencing samples

| EGAD00001004454 | EGA

ena-DATASET-KULVIB-04-03-2016-10:53:34:991-129 - samples

Project description:Firs 1106 16S rDNA data for the Flemish Gut Flora Project

| EGAD00001001936 | EGA

FGFP and TR-MDD shotgun sequencing samples (N=157)

Project description:Study exploring the neuroactive potential of the human gut microbiota in relation to quality of life and depression. This dataset includes shotgun sequenced samples from the FGFP (Flemish Gut Flora Project: N=150) and TR-MDD (Treatment-Resistant Major Depression Disorder: N=7). Samples were provided by volunteers from the Flanders region in Belgium, and the dataset is balanced for age, gender, and stool consistency.

| EGAS00001003298 | EGA

An European eel-specific microarray platform was developed to identify genes involved in response to pollutants

2013-05-22 | GSE41240 | GEO

An European eel-specific microarray platform was developed to identify genes involved in response to pollutants

Project description:An European eel-specific microarray platform was developed to identify genes involved in response to pollutants. A comparative analysis of gene expression was conducted between European eel Anguilla anguilla individuals from lowly-polluted Wijmeers pond at Uitbergen (Belgium), highly-polluted Hazewinkel pond at Willebroek (Belgium), extremely-polluted Dessel-Schotel canal at the locations of Schotel (Belgium) and low polluted Bolsena lake (Italy) environments. A comparative analysis of gene expression was conducted between European eel Anguilla anguilla individuals from lowly-polluted Wijmeers pond at Uitbergen (Belgium), highly-polluted Hazewinkel pond at Willebroek (Belgium), extremely-polluted Dessel-Schotel canal at the locations of Schotel (Belgium) and low polluted Bolsena lake (Italy) environments. Gene expression profiling was performed using an European eel-specific oligo-DNA microarray (GPL15124) of 14,913 probes based on single-colour detection (Cyanine-3 only). Microarrays were scanned with Agilent scanner G2565BA (barcode on the left, DNA on the back surface, scanned through the glass) at a resolution of 5 microns; all slides were scanned twice at two different sensitivity settings (XDRHi 100% and XDRLo 10%); the scanner software created a unique ID for each pair of XDR scans and saved it to both scan image files. Feature Extraction (FE) 9.5 used XDR ID to link the pairs of scans together automatically when extracting data. The signal left after all the FE processing steps have been completed is ProcessedSignal that contains the Multiplicatively Detrended, Background-Subtracted Signal.

2013-05-22 | E-GEOD-41240 | biostudies-arrayexpress

Genome wide associations of human gut microbiota variation and implications for causal inference analyses

Project description:Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

| EGAS00001004420 | EGA

RNA-seq data on leaf 8 blade tissue of 62 individual Brassica napus (Darmor) plants grown in the field.

Project description:62 individual Brassica napus plants of the same accession grown in the same field were expression-profiled in autumn 2016 and phenotyped extensively until harvest in spring 2017. Machine learning models were used to link gene expression to the phenotypes of individual plants, with the purpose of assessing how much phenotype information in encoded in ‘noisy’ gene expression variation among individual plants of the same background grown under the same uncontrolled field conditions. Rosette leaf 8 blades of 62 individual Brassica napus plants of the same winter-type accession (BnASSYST-120, Darmor) grown in the same field (50°58'24.9\\"N 3°46'49.1\\"E, Merelbeke, Belgium) were RNA-seq profiled. No treatments or stresses were applied, all plants were profiled individually under uncontrolled field conditions. Sown at 2016-09-08, rosette leaf 8 sampled for RNA-seq at 2016-11-28, plants harvested at 2017-06-13.

2022-10-10 | E-MTAB-11904 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data