Literature DB >> 33647928

CCmed: Cross-condition mediation analysis for identifying replicable trans-associations mediated by cis-gene expression.

Fan Yang1, Kevin J Gleason2, Jiebiao Wang3, Jubao Duan4,5, Xin He6, Brandon L Pierce2,6, Lin S Chen2.   

Abstract

MOTIVATION: Trans-acting expression quantitative trait loci (eQTLs) collectively explain a substantial proportion of expression variation, yet are challenging to detect and replicate since their effects are often individually weak. A large proportion of genetic effects on distal genes are mediated through cisgene expression. Cis-association (between SNP and cis-gene) and gene-gene correlation conditional on SNP genotype could establish trans-association (between SNP and trans-gene). Both cis-association and gene-gene conditional correlation have effects shared across relevant tissues and conditions, and transassociations mediated by cis-gene expression also have effects shared across relevant conditions.
RESULTS: . We proposed a Cross-Condition Mediation analysis method (CCmed) for detecting cis-mediated trans-associations with replicable effects in relevant conditions/studies. CCmed integrates cis-association and gene-gene conditional correlation statistics from multiple tissues/studies. Motivated by the bimodal effect-sharing patterns of eQTLs, we proposed two variations of CCmed, CCmedmost and CCmedspec for detecting cross-tissue and tissue-specific trans-associations, respectively. We analyzed data of 13 brain tissues from the Genotype-Tissue Expression (GTEx) project, and identified trios with cis-mediated transassociations across brain tissues, many of which showed evidence of trans-association in two replication studies. We also identified trans-genes associated with schizophrenia loci in at least two brain tissues.
AVAILABILITY AND IMPLEMENTATION: CCmed software is available at http://github.com/kjgleason/CCmed. SUPPLEMENTARY INFORMATION: Supplementary Material are available at Bioinformatics online.
© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Year:  2021        PMID: 33647928      PMCID: PMC8428610          DOI: 10.1093/bioinformatics/btab139

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  21 in total

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Journal:  Bioinformatics       Date:  2016-04-19       Impact factor: 6.937

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6.  A robust two-sample transcriptome-wide Mendelian randomization method integrating GWAS with multi-tissue eQTL summary statistics.

Authors:  Kevin J Gleason; Fan Yang; Lin S Chen
Journal:  Genet Epidemiol       Date:  2021-04-09       Impact factor: 2.344

7.  Integrative Tissue-Specific Functional Annotations in the Human Genome Provide Novel Insights on Many Complex Traits and Improve Signal Prioritization in Genome Wide Association Studies.

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8.  Bayesian test for colocalisation between pairs of genetic association studies using summary statistics.

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Authors:  Alexis Battle; Christopher D Brown; Barbara E Engelhardt; Stephen B Montgomery
Journal:  Nature       Date:  2017-10-11       Impact factor: 49.962

10.  Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits.

Authors:  Kevin J Gleason; Fan Yang; Brandon L Pierce; Xin He; Lin S Chen
Journal:  Genome Biol       Date:  2020-09-11       Impact factor: 13.583

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1.  Joint eQTL mapping and Inference of Gene Regulatory Network Improves Power of Detecting both cis- and trans-eQTLs.

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Journal:  Bioinformatics       Date:  2021-09-06       Impact factor: 6.931

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