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## ----loadPackages, echo=FALSE, warning=FALSE, message=FALSE-------------------
library(knitr)
library(pander)
suppressPackageStartupMessages(library(ramwas))
panderOptions("digits", 3)
opts_chunk$set(fig.width = 6, fig.height = 6)
# opts_chunk$set(eval=FALSE)
dr = "D:/temp/"
## ----generateData-------------------------------------------------------------
library(ramwas)
# work in a temporary directory
dr = paste0(tempdir(), "/simulated_matrix_data")
dir.create(dr, showWarnings = FALSE)
cat(dr,"\n")
## ----dims, eval=TRUE----------------------------------------------------------
nsamples = 200
nvariables = 100000
## ----setseed1, echo=FALSE-----------------------------------------------------
set.seed(18090212)
## ----genCovar-----------------------------------------------------------------
covariates = data.frame(
sample = paste0("Sample_",seq_len(nsamples)),
sex = seq_len(nsamples) %% 2,
age = runif(nsamples, min = 20, max = 80),
batch = paste0("batch",(seq_len(nsamples) %% 3))
)
pander(head(covariates))
## ----setseed2, echo=FALSE-----------------------------------------------------
set.seed(18090212)
## ----genLocs------------------------------------------------------------------
temp = cumsum(sample(20e7 / nvariables, nvariables, replace = TRUE) + 0)
chr = as.integer(temp %/% 1e7) + 1L
position = as.integer(temp %% 1e7)
locmat = cbind(chr = chr, position = position)
chrnames = paste0("chr", 1:10)
pander(head(locmat))
## ----locSave------------------------------------------------------------------
fmloc = fm.create.from.matrix(
filenamebase = paste0(dr, "/CpG_locations"),
mat = locmat)
close(fmloc)
writeLines(con = paste0(dr, "/CpG_chromosome_names.txt"), text = chrnames)
## ----setseed3, echo=FALSE-----------------------------------------------------
set.seed(18090212)
## ----fillDataMat--------------------------------------------------------------
fmm = fm.create(paste0(dr,"/Coverage"), nrow = nsamples, ncol = nvariables)
fms = fm.create(paste0(dr,"/SNPs"), nrow = nsamples, ncol = nvariables,
size = 1, type = "integer")
# Row names of the matrices are set to sample names
rownames(fmm) = as.character(covariates$sample)
rownames(fms) = as.character(covariates$sample)
# The matrices are filled, 2000 variables at a time
byrows = 2000
for( i in seq_len(nvariables/byrows) ){ # i=1
ind = (1:byrows) + byrows*(i-1)
snps = rbinom(n = byrows * nsamples, size = 2, prob = 0.2)
dim(snps) = c(nsamples, byrows)
fms[,ind] = snps
slice = double(nsamples*byrows)
dim(slice) = c(nsamples, byrows)
slice[, 1:225] = slice[, 1:225] + covariates$sex / 50 / sd(covariates$sex)
slice[,101:116] = slice[,101:116] + covariates$age / 16 / sd(covariates$age)
slice = slice +
((as.integer(factor(covariates$batch))+i) %% 3) / 200 +
snps / 1.5 +
runif(nsamples*byrows) / 2
fmm[,ind] = slice
}
close(fms)
close(fmm)
## ----paramMWAS, warning=FALSE, message=FALSE----------------------------------
param = ramwasParameters(
dircoveragenorm = dr,
covariates = covariates,
modelcovariates = "batch",
modeloutcome = "sex",
toppvthreshold = 20,
fileSNPs = "SNPs"
)
## ----threads, echo=FALSE------------------------------------------------------
# Bioconductor requires limit of 2 parallel jobs
param$cputhreads = 2
## ----SNPs, message=FALSE, warning=FALSE---------------------------------------
ramwasSNPs(param)
## ----plotQQ2, echo=FALSE, warning=FALSE, message=FALSE------------------------
pfull = parameterPreprocess(param)
mwas = getMWAS(pfull$dirSNPs)
qqPlotFast(mwas$`p-value`)
title("QQ-plot for CpG-SNP analysis")
## ----MWAS, message=FALSE, warning=FALSE---------------------------------------
ramwas5MWAS(param)
## ----plotQQ1, echo=FALSE, warning=FALSE, message=FALSE------------------------
mwas = getMWAS(param)
qqPlotFast(mwas$`p-value`)
title(pfull$qqplottitle)
## ----topPvSNPs----------------------------------------------------------------
# Get the directory with testing results
toptbl = read.table(
paste0(pfull$dirSNPs, "/Top_tests.txt"),
header = TRUE,
sep = "\t")
pander(head(toptbl,10))
## ----topPvMWAS----------------------------------------------------------------
pfull = parameterPreprocess(param)
toptbl = read.table(
paste0(pfull$dirmwas, "/Top_tests.txt"),
header = TRUE,
sep = "\t")
pander(head(toptbl,10))
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