Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the International Mouse Phenotyping Consortium

ABSTRACT: Untargeted and targeted metabolomics datasets were acquired for blood plasma samples of 30 mouse knockouts within the International Mouse Phenotyping Consortium (IMPC). http://www.mousephenotype.org/. West Coast Metabolomics Center at UC Davis (https://metabolomics.ucdavis.edu/) conducted the metabolomics analyses.

ORGANISM(S): Mouse Mus Musculus

TISSUE(S): Blood

SUBMITTER: Dinesh Barupal

PROVIDER: ST001154 | MetabolomicsWorkbench | Tue Mar 12 00:00:00 GMT 2019

REPOSITORIES: MetabolomicsWorkbench

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	mwtab	Other

Items per page:

1 - 1 of 1

Similar Datasets

Metabolomics Workbench ST001154 - GNPS - A comprehensive plasma metabolomics dataset for a cohort of mouse knockouts within the International Mouse Phenotyping Consortium

Project description:Untargeted and targeted metabolomics datasets were acquired for blood plasma samples of 30 mouse knockouts within the International Mouse Phenotyping Consortium (IMPC). http://www.mousephenotype.org/. West Coast Metabolomics Center at UC Davis (https://metabolomics.ucdavis.edu/) conducted the metabolomics analyses.

2019-07-01 | MSV000084039 | GNPS

ProMetIS: deep phenotyping of mouse models by proteomics and metabolomics

Project description:The ProMetIS dataset corresponds to the proteomic and metabolomic analysis of mouse lines lacking the LAT (linker for activation of T cells; OMIM: 602354) or MX2 gene (MX dynamin-like GTPase 2; OMIM: 147890), as well as the control (WT) line. Besides its role in T-cell receptor (TCR) signaling (Roncagalli et al., 2010), LAT has been shown to be involved in neurodevelopmental diseases (Loviglio et al., 2017). The systematic generation of mouse models is part of the functional characterization of the genome by the IMPC consortium (Brown et al., 2018). This characterization is currently based on a battery of animal phenotypic tests (anatomy, behaviour, histology, haematology, physiology), the results of which feed the IMPC database (https://www.mousephenotype.org). In particular, gene knockouts associated to metabolic diseases have been identified (Rozman et al., 2018). To further characterize these models, global molecular approaches are required, such as the metabolomics analysis of plasma samples which has been described recently (Barupal et al., 2019). The originality of ProMetIS is to provide, in addition to the clinical data, the proteomics and metabolomics analysis of the LAT, MX2 and WT mouse models in liver and plasma. ProMetIS provides access to unique molecular functional information on the LAT and MX2 genes. In addition, the dataset has been generated by the four national infrastructures for mouse phenogenomics (PHENOMIN-ICS), proteomics (ProFI), metabolomics (MetaboHUB) and bioinformatics (IFB) for optimal quality, reproducibility and accessibility. The protocols and computational workflows provided here can be easily extended to a larger number of individuals and tissues. Finally, ProMetIS will be of great interest to develop and evaluate bioinformatics and biostatistical methods for the processing and integration of proteomic and metabolomic data.

2021-11-11 | PXD028550 | Pride

ProMetIS: deep phenotyping of mouse models by proteomics and metabolomics.

Project description:We develop new tools enabling high-throughput and combined proteomics and metabolomics data analysis. The tools are validated on two knockout mice models (LAT (Linker For Activation Of T-Cells) and Mx2 KO mice) generated and phenotyped by the PHENOMIN infrastructure.

2021-11-18 | PXD028416 | Pride

An Integrated Metabolic Atlas of Clear Cell Renal Cell Carcinoma

Project description:Changes in cellular metabolism contribute to the development and progression of tumors, and can render tumors vulnerable to interventions. However, studies of human cancer metabolism remain limited due to technical challenges of detecting and quantifying small molecules, the highly interconnected nature of metabolic pathways, and the lack of designated tools to analyze and integrate metabolomics with other âomics data. Our study generates the largest comprehensive metabolomics dataset on a single cancer type, and provides a significant advance in integration of metabolomics with sequencing data. Our results highlight the massive re-organization of cellular metabolism as tumors progress and acquire more aggressive features. The results of our work are made available through an interactive public data portal for cancer research community. 10 RNA samples from human ccRCC tumors analyzed from the high glutathione cluster

2016-03-08 | E-GEOD-74734 | biostudies-arrayexpress

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density [Osteoclast_48H_samples]

Project description:The genetic landscape of diseases associated with changes in bone mineral density (BMD), such as osteoporosis, is only partially understood. Here, we explored the International Mouse Phenotyping Consortium (IMPC) for the analysis of skeletal data from 3,974 mutant strains for bone mineral density (BMD), a measure that is frequently altered in a range of bone pathologies including osteoporosis. A total of 200 genes were found to significantly affect BMD. This gene pool comprised 141 genes that were previously not known to have a function in bone biology and was complementary to pools derived from recent human studies. Nineteen of the 141 BMD genes also caused skeletal abnormalities. Further, evidence suggested a direct role for several of the identified BMD genes in osteoclasts and osteoblasts, and candidate genes for further investigation were prioritized. Overall, the results add novel pathophysiological and molecular insight into bone health and disease

2021-01-12 | GSE158149 | GEO

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density [Osteoblast_5days]

2021-01-12 | GSE158148 | GEO

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density [Unsorted_Osteoblast_7_17days]

2021-01-12 | GSE158147 | GEO

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density [Sorted_Osteoblast_7_17days]

2021-01-12 | GSE158146 | GEO

Mouse mutant phenotyping at scale reveals novel genes controlling bone mineral density [Osteoclast_0_3days]

2021-01-12 | GSE158150 | GEO

ENCODE H1_ES cell phenotyping study

Project description:These samples are part of the ENCODE consortium’s proposed time-limited Pilot Study for confirmation of the utility of RNA abundance measurements as a standard reference phenotyping tool. Keywords: cell type comparison For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Each batch of H1-ES cells cultured by Cellular Dynamics International for use by the ENCODE labs was processed on Affymetrix Exon 1.0 ST arrays to obtain phenotyping data.

2009-02-16 | E-GEOD-14863 | 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