--- title: "epimutacionsData: a data repostory for epimutacions package" author: "Leire Abarrategui" date: "`r doc_date()`" vignette: > %\VignetteIndexEntry{data repository for epimutacions package} %\VignetteEngine{knitr::rmarkdown} output: BiocStyle::html_document bibliography: refs.bib --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` # Introduction The `epimutacionsData` package is a repository of datasets for the `epimutacions` package. It includes 2 datasets to use as an example: * **Reference panel**: DNA methylation profiles of 24 whole cord blood samples from healthy children born via caesarian (GEO: GSE127824) * **Case and control samples**: DNA methylation profiling of whole blood samples in healthy children (GSE104812). CHARGE and Kabuki syndromes whole blood samples DNA methylation profiles (GEO: GSE97362). * **Candidate regions**: Regions in Illumina 450K array which are candidate to be epimutations. # Installation The following code explains how to access to the data: ```{r message = FALSE} library(ExperimentHub) eh <- ExperimentHub() query(eh, c("epimutacionsData")) ``` ## Candidate epimutations In Illumina 450K array [@reproducibilityinfinium], probes are unequally distributed along the genome, limiting the number of regions that can fulfil the requirements to be considered an epimutation. So, we have computed a dataset containing the regions that are candidates to become an epimutation. To define the candidate epimutations, we relied on the clustering from bumphunter [@jaffe2012bump]. We defined a primary dataset with all the CpGs from the Illumina 450K array. Then, we run bumphunter and selected those regions with at least 3 CpGs. As a result, we found 40408 candidate epimutations which are available in the `candRegsGR` dataset. ```{r message = FALSE, eval = FALSE} candRegsGR <- eh[["EH6692"]] ``` ## Example datasets ### Reference panel The package includes an `RGChannelSet` class reference panel (`reference_panel`) which contains 22 whole cord blood samples from healthy children born via caesarian from the GSE127824 cohort [@gervin2019systematic]. The reference panel can be found in `EH6691` record of the `eh` object: ```{r message = FALSE} reference_panel <- eh[["EH6691"]] ``` ### Control and case samples The `methy` dataset includes 51 DNA methylation profiling of whole blood samples. 48 controls from GSE104812 [@shi2018dna] cohort and 3 cases from GSE97362 [@butcher2017charge]. it is a `GenomicRatioSet` class object. ```{r message = FALSE} methy <- eh[["EH6690"]] ``` ## IDAT files The IDAT files contain raw microarray intensities of 4 case samples from GSE131350 cohort. The files are located on the external data of `epimutacionsData` package: ```{r, message = FALSE, eval = FALSE} library(minfi) baseDir <- system.file("extdata", package = "epimutacionsData") targets <- read.metharray.sheet(baseDir) ``` # sessionInfo() ```{r sessionInfo} sessionInfo() ``` # References