scholarly journals EWAS-Galaxy: a tools suite for population epigenetics integrated into Galaxy

2019 ◽  
Author(s):  
Katarzyna Murat ◽  
Björn Grüning ◽  
Paulina Wiktoria Poterlowicz ◽  
Gillian Westgate ◽  
Desmond J Tobin ◽  
...  

AbstractBackgroundEpigenome-wide association studies (EWAS) analyse genome-wide activity of epigenetic marks in cohorts of different individuals to find associations between epigenetic variation and phenotype. One of the most common technique used in EWAS studies is the Infinium Methylation Assay, which quantifies the DNA methylation level of over 450k loci. Although a number of bioinformatics tools have been developed to analyse the assay they require some programming skills and experience to use them.ResultsWe have developed a collection of user-friendly tools for the Galaxy platform for those without experience aimed at DNA methylation analysis using the Infinium Methylation Assay. Our tool suite is integrated into Galaxy (http://galaxyproject.org), web based platform. This allows users to analyse data from the Infinium Methylation Assay in the easiest possible way.ConclusionsThe EWAS suite provides a group of integrated tools that combine analytical methods into a range of handy analysis pipelines. Our tool suite is available from the Galaxy test toolshed, GitHub repository and also as a Docker image. The aim of this project is to make EWAS analysis more flexible and accessible to everyone.

GigaScience ◽  
2020 ◽  
Vol 9 (5) ◽  
Author(s):  
Katarzyna Murat ◽  
Björn Grüning ◽  
Paulina Wiktoria Poterlowicz ◽  
Gillian Westgate ◽  
Desmond J Tobin ◽  
...  

Abstract Background Infinium Human Methylation BeadChip is an array platform for complex evaluation of DNA methylation at an individual CpG locus in the human genome based on Illumina’s bead technology and is one of the most common techniques used in epigenome-wide association studies. Finding associations between epigenetic variation and phenotype is a significant challenge in biomedical research. The newest version, HumanMethylationEPIC, quantifies the DNA methylation level of 850,000 CpG sites, while the previous versions, HumanMethylation450 and HumanMethylation27, measured >450,000 and 27,000 loci, respectively. Although a number of bioinformatics tools have been developed to analyse this assay, they require some programming skills and experience in order to be usable. Results We have developed a pipeline for the Galaxy platform for those without experience aimed at DNA methylation analysis using the Infinium Human Methylation BeadChip. Our tool is integrated into Galaxy (http://galaxyproject.org), a web-based platform. This allows users to analyse data from the Infinium Human Methylation BeadChip in the easiest possible way. Conclusions The pipeline provides a group of integrated analytical methods wrapped into an easy-to-use interface. Our tool is available from the Galaxy ToolShed, GitHub repository, and also as a Docker image. The aim of this project is to make Infinium Human Methylation BeadChip analysis more flexible and accessible to everyone.


2014 ◽  
Vol 18 (1) ◽  
pp. 86-91 ◽  
Author(s):  
Aniket Mishra ◽  
Stuart Macgregor

Gene-based tests such as versatile gene-based association study (VEGAS) are commonly used following per-single nucleotide polymorphism (SNP) GWAS (genome-wide association studies) analysis. Two limitations of VEGAS were that the HapMap2 reference set was used to model the correlation between SNPs and only autosomal genes were considered. HapMap2 has now been superseded by the 1,000 Genomes reference set, and whereas early GWASs frequently ignored the X chromosome, it is now commonly included. Here we have developed VEGAS2, an extension that uses 1,000 Genomes data to model SNP correlations across the autosomes and chromosome X. VEGAS2 allows greater flexibility when defining gene boundaries. VEGAS2 offers both a user-friendly, web-based front end and a command line Linux version. The online version of VEGAS2 can be accessed through https://vegas2.qimrberghofer.edu.au/. The command line version can be downloaded from https://vegas2.qimrberghofer.edu.au/zVEGAS2offline.tgz. The command line version is developed in Perl, R and shell scripting languages; source code is available for further development.


BMC Genomics ◽  
2020 ◽  
Vol 21 (S3) ◽  
Author(s):  
Sheng-Yao Su ◽  
I-Hsuan Lu ◽  
Wen-Chih Cheng ◽  
Wei-Chun Chung ◽  
Pao-Yang Chen ◽  
...  

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jochen Kruppa ◽  
Miriam Sieg ◽  
Gesa Richter ◽  
Anne Pohrt

Abstract Background In DNA methylation analyses like epigenome-wide association studies, effects in differentially methylated CpG sites are assessed. Two kinds of outcomes can be used for statistical analysis: Beta-values and M-values. M-values follow a normal distribution and help to detect differentially methylated CpG sites. As biological effect measures, differences of M-values are more or less meaningless. Beta-values are of more interest since they can be interpreted directly as differences in percentage of DNA methylation at a given CpG site, but they have poor statistical properties. Different frameworks are proposed for reporting estimands in DNA methylation analysis, relying on Beta-values, M-values, or both. Results We present and discuss four possible approaches of achieving estimands in DNA methylation analysis. In addition, we present the usage of M-values or Beta-values in the context of bioinformatical pipelines, which often demand a predefined outcome. We show the dependencies between the differences in M-values to differences in Beta-values in two data simulations: a analysis with and without confounder effect. Without present confounder effects, M-values can be used for the statistical analysis and Beta-values statistics for the reporting. If confounder effects exist, we demonstrate the deviations and correct the effects by the intercept method. Finally, we demonstrate the theoretical problem on two large human genome-wide DNA methylation datasets to verify the results. Conclusions The usage of M-values in the analysis of DNA methylation data will produce effect estimates, which cannot be biologically interpreted. The parallel usage of Beta-value statistics ignores possible confounder effects and can therefore not be recommended. Hence, if the differences in Beta-values are the focus of the study, the intercept method is recommendable. Hyper- or hypomethylated CpG sites must then be carefully evaluated. If an exploratory analysis of possible CpG sites is the aim of the study, M-values can be used for inference.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel L. McCartney ◽  
Josine L. Min ◽  
Rebecca C. Richmond ◽  
Ake T. Lu ◽  
Maria K. Sobczyk ◽  
...  

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.


2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Xiao-Long Yuan ◽  
Zhe Zhang ◽  
Bin Li ◽  
Ning Gao ◽  
Hao Zhang ◽  
...  

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