Source: TBA

Introduction

baseDir=getwd()
dataDir=paste(baseDir,"/him_chart_idats/HIM_idats",sep="")

suppressPackageStartupMessages({
  library("missMethyl")
  library("limma")
  library("minfi")
  library("IlluminaHumanMethylation450kanno.ilmn12.hg19")
  library("IlluminaHumanMethylationEPICanno.ilm10b2.hg19")
  library("ruv")
  library("RColorBrewer")
  library("matrixStats")
  library("gplots")
  library("FlowSorted.Blood.450k")
  library("reshape2")
  library("ggplot2")
  library("DMRcate")
  library("FlowSorted.Blood.EPIC")
  library("mitch")
  library("kableExtra")
  library("vioplot")
})

#source("meth_functions.R")

Load data

Load the annotation data and the Epic methylation data.

This analysis is to be conducted on Ubuntu with R4.

ann = getAnnotation(IlluminaHumanMethylationEPICanno.ilm10b2.hg19)

ann_sub = ann[,c("chr","pos","strand","Name","Islands_Name",
    "Relation_to_Island","UCSC_RefGene_Name","UCSC_RefGene_Group")]

targets_gen = read.metharray.sheet(dataDir, pattern = "HIM_EPIC_sampleSheet.csv")
## [read.metharray.sheet] Found the following CSV files:
## [1] "/analysis/him_chart_idats/HIM_idats/HIM_EPIC_sampleSheet.csv"
#targets$ID = paste(targets$Sample_Group,targets_gen$Sample_Name,sep=".")
rgSet = read.metharray.exp(targets = targets_gen)
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sampleNames(rgSet) = targets_gen$Sample_Name

rgSet$Slide <- as.numeric(rgSet$Slide)
rgSet$Gender <- as.character(rgSet$Gender)
rgSet$Sex <- as.character(rgSet$Gender)
rgSet$Sample_Name<- as.character(rgSet$Sample_Name)

Testing familial structure

snpBetas = getSnpBeta(rgSet)
## Loading required package: IlluminaHumanMethylationEPICmanifest
d = dist(t(snpBetas))
hr = hclust(d, method = "complete", members=NULL)
plot(hr)

Quality control

detP = detectionP(rgSet)
qcReport(rgSet, sampNames = targets_gen$Sample_Name,
  pdf="qc-report_him.pdf")
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## caller; using TRUE

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## Warning: SPECIFICITY I probes outside plot range
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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## caller; using TRUE

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## png 
##   2
cols=brewer.pal(4,"Set1")

barplot(apply(detP,2,mean),
  col=as.numeric(factor(targets_gen$Sample_Name)),
  las=2,cex.names= 0.8, cex.axis=0.75,
  main="Mean detection p-values of probe signals",
  ylab="Mean detection p-value")