eQTL-Search
Version 1

External Link

This shiny app facilitates the download and searching of the summary statistics from "Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding loci" (https://doi.org/10.1093/hmg/ddv194).

LHA ID: 82YFJKN2CW-7

1 item is associated with this Model:

Human Disease: Not specified

Model type: Not specified

Model format: R package

Execution or visualisation environment: Shiny


Try App

Model image: No image specified

Help
help Creators and Submitter
Creators
Additional credit

Holger Kirsten

Submitter
License
Creative Commons Attribution 4.0
Activity

Views: 2300

Created: 8th Jul 2020 at 12:17

Last updated: 8th Jul 2020 at 12:22

Last used: 20th Nov 2024 at 12:09

help Tags

This item has not yet been tagged.

help Attributions

None

Version History

Version 1 Created 8th Jul 2020 at 12:17 by Carl Beuchel

No revision comments

Related items

Genetical Statistics and Systems Biology

The group is interested in omic-level studies including the genome, methylome, transcriptome, and metabolome of the general population as well as of various diseases including cardiovascular diseases, pneumonia, sepsis, obesity, and brain cancers. Additionally, we aim at transfering results of biomathematical model simulations into clinical practice e.g. by haematopoietic growth-factor opimization during cytotoxic chemotherapy and optimization of EPO applications in chronic kidney disease.

The ...

Programme: This Project is not associated with a Programme

Public web page: http://www.imise.uni-leipzig.de/en/Groups/GenStat/

Start date: 1st Jan 2013

Dissecting the genetics of the human transcriptome identifies novel trait-related trans-eQTLs and corroborates the regulatory relevance of non-protein coding locidagger.
Genetical Statistics and Systems Biology, LIFE Heart

Abstract (Expand)

Genetics of gene expression (eQTLs or expression QTLs) has proved an indispensable tool for understanding biological pathways and pathomechanisms of trait-associated SNPs. However, power of most … genome-wide eQTL studies is still limited. We performed a large eQTL study in peripheral blood mononuclear cells of 2112 individuals increasing the power to detect trans-effects genome-wide. Going beyond univariate SNP-transcript associations, we analyse relations of eQTLs to biological pathways, polygenetic effects of expression regulation, trans-clusters and enrichment of co-localized functional elements. We found eQTLs for about 85% of analysed genes, and 18% of genes were trans-regulated. Local eSNPs were enriched up to a distance of 5 Mb to the transcript challenging typically implemented ranges of cis-regulations. Pathway enrichment within regulated genes of GWAS-related eSNPs supported functional relevance of identified eQTLs. We demonstrate that nearest genes of GWAS-SNPs might frequently be misleading functional candidates. We identified novel trans-clusters of potential functional relevance for GWAS-SNPs of several phenotypes including obesity-related traits, HDL-cholesterol levels and haematological phenotypes. We used chromatin immunoprecipitation data for demonstrating biological effects. Yet, we show for strongly heritable transcripts that still little trans-chromosomal heritability is explained by all identified trans-eSNPs; however, our data suggest that most cis-heritability of these transcripts seems explained. Dissection of co-localized functional elements indicated a prominent role of SNPs in loci of pseudogenes and non-coding RNAs for the regulation of coding genes. In summary, our study substantially increases the catalogue of human eQTLs and improves our understanding of the complex genetic regulation of gene expression, pathways and disease-related processes.

Authors: H. Kirsten, H. Al-Hasani, L. Holdt, A. Gross, F. Beutner, K. Krohn, K. Horn, P. Ahnert, R. Burkhardt, K. Reiche, J. Hackermuller, M. Loffler, D. Teupser, J. Thiery, M. Scholz

Date Published: 15th Aug 2015

Publication Type: Journal article

Navigate

Health Atlas - Local Data Hub/Leipzig

The Health Atlas - Local Data Hub/Leipzig is an alliance of medical ontologists, medical systems biologists and clinical trials groups to design and implement a multi-functional and quality-assured atlas. It provides models, data and metadata on specific use cases from medical research fields.

Registered Repository

re3data.org Badge
Powered by
 (v.1.13.0-master)
Health Atlas | Funding and Programmes | Credits | Terms & Conditions | Privacy Policy | Imprint
Copyright © 2008 - 2021 The University of Manchester and HITS gGmbH
Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig

By continuing to use this site you agree to the use of cookies