Epigenome-wide association study software tools | Bisulfite sequencing data analysis
The goal of epigenome-wide association studies (EWAS), analogous to that of genome-wide association studies (GWAS), is to identify changes in the epigenome at particular loci that are correlated with a phenotype of interest.
Permits reference-free deconvolution. RefFreeEWAS offers a method for evaluating the extent to which the underlying reflects specific types of cells. It differs from widely used principal components analysis (PCA)-based methods such as Surrogate Variable Analysis (SVA) in imposing biologically based constraints, thus resulting in mixture coefficients having greater biological interpretation and placing greater emphasis on coordinated cellular processes.
Identifies the cell type-specific regulatory component of a set of epigenome wide association studies (EWAS)-identified differentially methylated positions. eFORGE generates a background of 1,000 random probe sets with matching properties regarding their location within genes and CpG islands. It shows rigorous performance assessment with regards to false-positive rates and speed to ensure ability to cope with high user demand. All results produced by the tool are highly reproducible.
A method based on principal component analysis (PCA) and designed for the correction of cell type heterogeneity in epigenome-wide association studies (EWAS). ReFACTor tool is based on a variant of PCA and can be applied to any tissue. It selects the sites that can be reconstructed with low error using a low-rank approximation of the original methylation matrix. Moreover, ReFACTor does not use the phenotype in the selection process, making ReFACTor useful as part of a quality control step in EWAS.
Incorporates combined signals in mean and variance differences of DNA methylation data. In the proposed NEpiC algorithm, we first compute mean and variance signal scores for a CpG site and then summarize the two scores with weights to create a combined score for the CpG site. We then extract the gene-level score out of all CpG sites on a gene. Finally, using a protein protein interction (PPI) network, we search for dense modules that are enriched for genes with large gene-level scores with a greedy search algorithm. Results from both simulations and real data applications demonstrate a much better performance of the NEpiC algorithm compared to several other methods that ignore either the biological network information or variance signals in DNA methylation data.
Provides a resource to the community to aid interpretation of blood based DNA methylation results in the context of brain tissue. BECon provides metrics data on: the variability of CpGs in blood and brain samples, the concordance of CpGs between blood and brain, and estimations of how strongly a CpG is affected by cell composition in both blood and brain. This data come from paired samples from 16 individuals from three brain regions and whole blood, run on the Illumina 450K Human Methylation Array to quantify the concordance of DNA methylation between tissues. It is expected that BECon will be useful to users who need to interpret blood DNAm results from a study of brain function and health. This application may also help guide blood based surrogate studies toward candidate gene approaches or post-hoc selection of CpGs for validation.
An R version of FaST-LMM-EWASher, which performs epigenome-wide association analysis in the presence of confounders such as cell-type heterogeneity. A python version of this software is also available as part of Fast-LMM-Py.
Maximizes power while properly controlling the false positive rate. Bacon is based on the estimation of the empirical null distribution using Bayesian statistics. The utility of the tool was illustrated through the application of meta-analysis by performing epigenome- and transcriptome-wide association studies (EWASs/TWASs) on age and smoking which highlighted an overlap in differential methylation and expression of associated genes. It can be used to remove inflation and bias often observed in EWAS/TWAS.