scholarly journals deTS: tissue-specific enrichment analysis to decode tissue specificity

2019 ◽  
Vol 35 (19) ◽  
pp. 3842-3845 ◽  
Author(s):  
Guangsheng Pei ◽  
Yulin Dai ◽  
Zhongming Zhao ◽  
Peilin Jia
Keyword(s):  
Expression Profiles ◽  
Association Studies ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
R Package ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide ◽  
Specific Regulation

Abstract Motivation Diseases and traits are under dynamic tissue-specific regulation. However, heterogeneous tissues are often collected in biomedical studies, which reduce the power in the identification of disease-associated variants and gene expression profiles. Results We present deTS, an R package, to conduct tissue-specific enrichment analysis with two built-in reference panels. Statistical methods are developed and implemented for detecting tissue-specific genes and for enrichment test of different forms of query data. Our applications using multi-trait genome-wide association studies data and cancer expression data showed that deTS could effectively identify the most relevant tissues for each query trait or sample, providing insights for future studies. Availability and implementation https://github.com/bsml320/deTS and CRAN https://cran.r-project.org/web/packages/deTS/ Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Tissue-Specific Enrichment Analysis (TSEA) to decode tissue specificity

2018 ◽  
Author(s):  
Guangsheng Pei ◽  
Yulin Dai ◽  
Zhongming Zhao ◽  
Peilin Jia
Keyword(s):  
Tissue Specificity ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Enrichment Analysis ◽  
R Package ◽  
Tissue Specific ◽  
Genome Wide ◽  
Specific Regulation ◽  
Association Data ◽  
Heterogeneous Tissues

AbstractMotivationDiseases and traits are under dynamic tissue-specific regulation. However, heterogeneous tissues are often collected in biomedical studies, which reduce the power in the identification of disease-associated variants and gene expression profiles.ResultsWe present TSEA, an R package to conduct Tissue-Specific Enrichment Analysis (TSEA) with two built-in reference panels. Statistical methods are developed and implemented for detecting tissue-specific genes and for enrichment test of different forms of query data. Our applications using multi-trait genome-wide association data and cancer expression data showed that TSEA could effectively identify the most relevant tissues for each query trait or sample, providing insights for future studies.Availabilityhttps://github.com/bsml320/[email protected] or [email protected]

scholarly journals bGWAS: an R package to perform Bayesian genome wide association studies

2020 ◽  
Vol 36 (15) ◽  
pp. 4374-4376
Author(s):  
Ninon Mounier ◽  
Zoltán Kutalik
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
R Package ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Biological Mechanisms ◽  
Genome Wide ◽  
Related Risk

Abstract Summary Increasing sample size is not the only strategy to improve discovery in Genome Wide Association Studies (GWASs) and we propose here an approach that leverages published studies of related traits to improve inference. Our Bayesian GWAS method derives informative prior effects by leveraging GWASs of related risk factors and their causal effect estimates on the focal trait using multivariable Mendelian randomization. These prior effects are combined with the observed effects to yield Bayes Factors, posterior and direct effects. The approach not only increases power, but also has the potential to dissect direct and indirect biological mechanisms. Availability and implementation bGWAS package is freely available under a GPL-2 License, and can be accessed, alongside with user guides and tutorials, from https://github.com/n-mounier/bGWAS. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Multi-SNP mediation intersection-union test

2019 ◽  
Vol 35 (22) ◽  
pp. 4724-4729 ◽  
Author(s):  
Wujuan Zhong ◽  
Cassandra N Spracklen ◽  
Karen L Mohlke ◽  
Xiaojing Zheng ◽  
Jason Fine ◽  
...  
Keyword(s):  
Association Studies ◽  
R Package ◽  
Alternative Methods ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Mediation Effects ◽  
Coding Regions ◽  
Genome Wide ◽  
Plasma Adiponectin Level ◽  
Intersection Union Test

Abstract Summary Tens of thousands of reproducibly identified GWAS (Genome-Wide Association Studies) variants, with the vast majority falling in non-coding regions resulting in no eventual protein products, call urgently for mechanistic interpretations. Although numerous methods exist, there are few, if any methods, for simultaneously testing the mediation effects of multiple correlated SNPs via some mediator (e.g. the expression of a gene in the neighborhood) on phenotypic outcome. We propose multi-SNP mediation intersection-union test (SMUT) to fill in this methodological gap. Our extensive simulations demonstrate the validity of SMUT as well as substantial, up to 92%, power gains over alternative methods. In addition, SMUT confirmed known mediators in a real dataset of Finns for plasma adiponectin level, which were missed by many alternative methods. We believe SMUT will become a useful tool to generate mechanistic hypotheses underlying GWAS variants, facilitating functional follow-up. Availability and implementation The R package SMUT is publicly available from CRAN at https://CRAN.R-project.org/package=SMUT. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals VarGen: an R package for disease-associated variant discovery and annotation

2019 ◽  
Vol 36 (8) ◽  
pp. 2626-2627
Author(s):  
Corentin Molitor ◽  
Matt Brember ◽  
Fady Mohareb
Keyword(s):  
Association Studies ◽  
Genetic Disorders ◽  
R Package ◽  
Tissue Expression ◽  
Mendelian Inheritance ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Variant Discovery ◽  
Genome Wide ◽  
High Quality Information

Abstract Summary Over the past decade, there has been an exponential increase in the amount of disease-related genomic data available in public databases. However, this high-quality information is spread across independent sources and researchers often need to access these separately. Hence, there is a growing need for tools that gather and compile this information in an easy and automated manner. Here, we present ‘VarGen’, an easy-to-use, customizable R package that fetches, annotates and rank variants related to diseases and genetic disorders, using a collection public databases (viz. Online Mendelian Inheritance in Man, the Functional Annotation of the Mammalian genome 5, the Genotype-Tissue Expression and the Genome Wide Association Studies catalog). This package is also capable of annotating these variants to identify the most impactful ones. We expect that this tool will benefit the research of variant-disease relationships. Availability and implementation VarGen is open-source and freely available via GitHub: https://github.com/MCorentin/VarGen. The software is implemented as an R package and is supported on Linux, MacOS and Windows. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals TWENTY-FOUR GENES ARE UPREGULATED IN PATIENTS WITH HYPOSPADIAS

2013 ◽  
Vol 16 (2) ◽  
pp. 39-43 ◽  
Author(s):  
R. Karabulut ◽  
Z. Turkyilmaz ◽  
K. Sonmez ◽  
G. Kumas ◽  
Sg. Ergun ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Association Studies ◽  
Gene Expression Profiles ◽  
Ventral Surface ◽  
Genome Wide Association Studies ◽  
Expression Array ◽  
Large Patient ◽  
Expression Studies ◽  
Genome Wide

ABSTRACT Hypospadias is a congenital hypoplasia of the penis, with displacement of the urethral opening along the ventral surface, and has been reported to be one of the most common congenital anomalies, occurring in approximately 1:250 to 1:300 live births. As hypospadias is reported to be an easily diagnosed malformation at the crossroads of genetics and environment, it is important to study the genetic component in order to elucidate its etiology. In this study, the gene expression profiles both in human hypospadias tissues and normal penile tissues were studied by Human Gene Expression Array. Twentyfour genes were found to be upregulated. Among these, ATF3 and CYR61 have been reported previously. Other genes that have not been previously reported were also found to be upregulated: BTG2, CD69, CD9, DUSP1, EGR1, EIF4A1, FOS, FOSB, HBEGF, HNRNPUL1, IER2, JUN, JUNB, KLF2, NR4A1, NR4A2, PTGS2, RGS1, RTN4, SLC25A25, SOCS3 and ZFP36 (p <0.05). Further studies including genome-wide association studies (GWAS) with expression studies in a large patient group will help us for identifiying the candidate gene(s) in the etiology of hypospadias

scholarly journals Mixed Logistic Regression in Genome-Wide Association Studies

2020 ◽  
Author(s):  
Jacqueline Milet ◽  
Hervé Perdry
Keyword(s):  
Logistic Regression ◽  
Linear Models ◽  
Association Studies ◽  
Score Test ◽  
R Package ◽  
Genome Wide Association ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Mixed Linear Models ◽  
Genome Wide

AbstractMotivationMixed linear models (MLM) have been widely used to account for population structure in case-control genome-wide association studies, the status being analyzed as a quantitative phenotype. Chen et al. proved that this method is inappropriate and proposed a score test for the mixed logistic regression (MLR). However this test does not allow an estimation of the variants’ effects.ResultsWe propose two computationally efficient methods to estimate the variants’ effects. Their properties are evaluated on two simulations sets, and compared with other methods (MLM, logistic regression). MLR performs the best in all circumstances. The variants’ effects are well evaluated by our methods, with a moderate bias when the effect sizes are large. Additionally, we propose a stratified QQ-plot, enhancing the diagnosis of p-values inflation or deflation, when population strata are not clearly identified in the sample.AvailabilityAll methods are implemented in the R package milorGWAS available at https://github.com/genostats/[email protected] informationSupplementary data are available at Bioinformatics online.

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