Help with EPIC methylation array data analysis - minfi, noob and dmpfinder
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4.8 years ago
veronico ▴ 70

I have EPIC data from 8 samples.

Sample sheet: Sorry I am new to posting here, so please forgive my bad formatting:

Plate   Bead chip # Well Position   Well Position   Sentrix_ID  Array   Complete Barcode    Sample_Name
1447    1   A01 01A 201172520042    R01C01  201172520042_R01C01 MCF10A N 2d
1447    1   B01 01B 201172520042    R02C01  201172520042_R02C01 MCF10A H 0.5% 2d
1447    1   C01 01C 201172520042    R03C01  201172520042_R03C01 68 N 2d
1447    1   D01 01D 201172520042    R04C01  201172520042_R04C01 68 H 4% 2d
1447    1   E01 01E 201172520042    R05C01  201172520042_R05C01 68 H 0.5% 2d
1447    1   F01 01F 201172520042    R06C01  201172520042_R06C01 68 N 8 wk
1447    1   G01 01G 201172520042    R07C01  201172520042_R07C01 68 N 3d
1447    1   H01 01H 201172520042    R08C01  201172520042_R08C01 68 H 4% 8wk

I am trying to find DMPs from the samples N 8 wk and H 4% 8wk. I did the following for normalizing and processing:

setwd("~/Desktop/HYPNOR/")

baseDir <- file.path("~/Desktop/HYPNOR/")
list.files(file.path(baseDir, "201172520042"))
list.files(file.path(baseDir))

targets <- read.metharray.sheet(baseDir)

RGset <- read.metharray.exp(targets = targets)
RGset
phenoData <- pData(RGset)
phenoData[,1:6]

pd <- pData(RGset)
pd
pd[,1:4]

qcReport(RGset, sampNames = pd$Sample_Name, pdf = "qcReport.pdf")

#Preprocessing/Normalizing/DYE correction
noob <- preprocessNoob(RGset)
RGset
GMset_map <- mapToGenome(noob)
snp_add <- addSnpInfo(GMset_map)

remove_snps <- dropLociWithSnps(snp_add, snps=c("SBE","CpG"), maf=0.05)

dmpFinder(remove_snps, pheno = pd$Sample_Group, type = c("categorical"))

What I have tried hasn't worked and I don't know how to single those two samples only for dmpfinder. I made a new sample sheet with just the two samples, but that didn't work and also created a subset of the data, and that didn't work.

I was wondering if there is a better solution for this? I am quite new to EPIC methylation analysis, so my apologies if I sound naive.

Any help would be awesome, please. Thank you.

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