Getting Started Installation - GianlucaMattei/methyl.O GitHub Wiki
Getting started
Installation:
The R release version of methyl.O is available via Bioconductor and GitHub. It can be installed as follow:
Documentation and Contacts
**Reserve 30 min troubleshooting meeting **
Introduction
During the last years the adaptation of next generation sequencing technologies to epigenetic studies has revolutionized the ability to study the methylation status of DNA. Despite the development of new techniques and the increasing interest in epigenomic, the landscape of available tools does not offer a wide range of possibilities for annotation. Here we present methyl.O, a R package and an online tool focused on interpretations of methylation analysis. While the practical user interface benefits non- bioinformatic users, the R package allows those more experienced to perform methylation analyses with more in-depth control over parameters. The user interface can also be run in local by R, to facilitate preliminary analyses and to easily visualize data distribution and methylated gene regions. A peculiarity of methyl.O results is the ranked list of the genes most affected by methylation and, according to available databases, most involved in pathologies. The ranked list suggests the genes to focus on to understand methylation effects and to consider for further analyses. Furthermore methyl.O allows, when expression profiles are provided, to compare transcriptomics to methylome to have a deeper insight into the resulting phenotype. methyl.O also offers the possibility to perform enrichment analysis, based on the package EnrichR, for a better interpretation of results. Finally, among the peculiarities that we implemented in our tool, the possibility to annotate enhancers and TFs to genes in order to predict the effects on expression. Moreover, both enhancers and TFs results can be integrated with expression profiles for a better understanding of the impact that methylation of these elements may lead to.
Getting started
Installation:
The R release version of methyl.O is available via Bioconductor and GitHub. It can be installed as follow:
GitHub:
devtools::install_github("GianlucaMattei/methyl.O", dependencies = TRUE)
Local:
Download the tar.gz file from
https://github.com/GianlucaMattei/methyl.O/releases/download/1.0/methyl.O.tar.gz
https://github.com/GianlucaMattei/methyl.O/releases/download/1.0/methyl.O.tar.gz
then install the package from local directory in R:
install.packages("path/to/tar.gz", repos=NULL)
Run interface:
Once the package is installed, using the function runOnDesktop() it is possible to initialize the user interface.
Online interface:
methyl.O is also available online at: www.genomica.pro
Required inputs:
R:
To run methyl.O you need a data.frame object with the genomic coordinates (chr, start and end) on the first three columns and the beta difference values on the fourth column. Specific beta values for the samples, used to score the beta difference values, are optional but recommended. The Beta difference values must be a fraction of 1. Additional columns will be stored in output under the "others" field
| seqnames | start | end | betadiff | betaTum | betaHlt | pval |
|---|---|---|---|---|---|---|
| chr10 | 38300277 | 38300763 | -0.355 | 0.474 | 0.031 | 0.030 |
| chr10 | 43725576 | 43725884 | 0.301 | 0.333 | 0.8125 | 0.010 |
| chr10 | 50886863 | 50887851 | 0.396 | 0.222 | 0.785 | 0.001 |
| chr10 | 105343883 | 105344827 | 0.315 | 0.058 | 0.35 | 0.003 |
| chr10 | 105728786 | 105730463 | -0.386 | 0.75 | 0.181 | 0.032 |
| chr10 | 115999356 | 115999894 | 0.384 | 0 | 0.636 | 0.020 |
GUI:
Otherwise in the GUI’s Homepage is possible to upload custom files specifying the delimiter type and if it already includes the names of the columns (header) and, if expressed as a percentage , to convert the beta difference values to a fraction of 1.
Basic Concepts
Gene Model and Gene’s Features:
Each is based on the classical gene model, which includes the promoter, the 5’/3’ UTRs and the exons/introns, and additional features specific to the methylation: the head of the gene and the TSS surrounding region. While the head corresponds to the first part of the gene, the TSS surrounding region results from considering the promoter and the head as a single range where methylation may have a greater effect on gene expression. As shown in the figure 1, by considering TSS surrounding or head regions for the annotation it is possible to avoid overlapping features. In fact, in some cases, the 5’ and the 3’ UTRs may overlap part of the first and last exon respectively (A), they can coincide with the first and the last exon or they can be absent (B) and in other cases they can overlap more than one exons (C). Thus considering only the 5’UTRs will exclude some genes while considering both 5’UTR and the first exons will lead to redundant results.