## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( fig.width = 8, collapse = TRUE, comment = "#>" ) ## ----style, echo = FALSE, results = 'asis'------------------------------------ BiocStyle::markdown() ## ----setup, message=F--------------------------------------------------------- library(knitr) ## ----Information on CpGs in MEAT, eval=FALSE---------------------------------- # data("CpGs_in_MEAT",envir = environment()) ## ----Information on CpGs in MEAT2.0, eval=FALSE------------------------------- # data("CpGs_in_MEAT2.0",envir = environment()) ## ----MEAT package installation, eval=FALSE------------------------------------ # if (!requireNamespace("BiocManager", quietly=TRUE)) # install.packages("BiocManager") # BiocManager::install("MEAT") ## ----MEAT package installation loading, message=FALSE, warning=FALSE---------- library(MEAT) ## ----Methylation matrix presentation------------------------------------------ data("GSE121961", envir = environment()) ## ----Methylation matrix presentation table, echo = FALSE---------------------- kable(head(GSE121961), caption = "Top rows of the GSE121961 matrix before cleaning and calibration.") ## ----Phenotype table presentation--------------------------------------------- data("GSE121961_pheno", envir = environment()) ## ----Phenotype table presentation table, echo = FALSE------------------------- kable(GSE121961_pheno, caption = "Phenotypes corresponding to GSE121961.") ## ----Data formatting, message=FALSE, warning=FALSE---------------------------- library(SummarizedExperiment) GSE121961_SE <- SummarizedExperiment(assays=list(beta=GSE121961), colData=GSE121961_pheno) GSE121961_SE ## ----Data cleaning, message=FALSE, warning=FALSE------------------------------ GSE121961_SE_clean <- clean_beta(SE = GSE121961_SE, version = "MEAT2.0") ## ----Data cleaning table, echo = FALSE---------------------------------------- kable(head(assays(GSE121961_SE_clean)$beta), caption = "Top rows of the GSE121961 beta matrix after cleaning.") ## ----Data calibration, message=FALSE, warning=FALSE--------------------------- GSE121961_SE_calibrated <- BMIQcalibration(SE = GSE121961_SE_clean, version = "MEAT2.0") ## ----Data calibration table, echo=FALSE--------------------------------------- kable(head(assays(GSE121961_SE_calibrated)$beta), caption = "Top rows of the GSE121961 beta matrix after cleaning and calibration.") ## ----DNA methylation profile distribution before and after calibration, message=FALSE, warning=FALSE---- data("gold.mean.MEAT2.0", envir = environment()) GSE121961_SE_clean_with_gold_mean <- cbind(assays(GSE121961_SE_clean)$beta, gold.mean.MEAT2.0$gold.mean) # add the gold mean GSE121961_SE_calibrated_with_gold_mean <- cbind(assays(GSE121961_SE_calibrated)$beta, gold.mean.MEAT2.0$gold.mean) # add the gold mean groups <- c(rep("GSE121961", ncol(GSE121961_SE_clean)), "Gold mean") library(minfi) par(mfrow = c(2, 1)) densityPlot(GSE121961_SE_clean_with_gold_mean, sampGroups = groups, main = "Before calibration", legend = FALSE ) densityPlot(GSE121961_SE_calibrated_with_gold_mean, sampGroups = groups, main = "After calibration" ) ## ----Epigenetic age estimation with phenotypes, message=FALSE, warning=FALSE---- GSE121961_SE_epiage <- epiage_estimation(SE = GSE121961_SE_calibrated, age_col_name = "Age", version = "MEAT2.0") ## ----Epigenetic age estimation with phenotypes table, echo=FALSE-------------- kable(colData(GSE121961_SE_epiage), caption = "Phenotypes corresponding to GSE121961 with AAdiff for each sample.") ## ----session info------------------------------------------------------------- sessionInfo()