inst/doc/mdts.R

In MDTS: Detection of de novo deletion in targeted sequencing trios

## ---- echo=F, message=F, warning=F--------------------------------------------
library(MDTS); library(BSgenome.Hsapiens.UCSC.hg19)
setwd(system.file("extdata", package="MDTS"))
load('pD.RData')
pD

## ---- echo=FALSE, message=FALSE-----------------------------------------------
library(MDTS)

## ---- eval=F, warning=F-------------------------------------------------------
#  library(MDTS); library(BSgenome.Hsapiens.UCSC.hg19)
#  # Using the raw data from MDTSData
#  devtools::install_github("jmf47/MDTSData")
#  setwd(system.file("data", package="MDTSData"))
#  
#  # Importing the pedigree file that includes information on where to locate the
#  # raw bam files
#  pD <- getMetaData("pD.ped")
#  
#  # Information on the GC content and mappability to estimate GC and mappability
#  # for the MDTS bins
#  genome <- BSgenome.Hsapiens.UCSC.hg19; map_file = "chr1.map.bw"
#  
#  # This command now subsets 5 samples to determine MDTS bins
#  # pD is the metaData matrix from getMetaData()
#  # n is the number of samples to examine to calculate the bins
#  # readLength is the sequencing read length
#  # minimumCoverage is the minimum read depth for a location to be included
#  #     in a proto region
#  # medianCoverage is the median number of reads across the n samples in a bin
#  bins <- calcBins(metaData=pD, n=5, readLength=100, minimumCoverage=5,
#                  medianCoverage=150, genome=genome, mappabilityFile=map_file)

## ---- eval=F------------------------------------------------------------------
#  # pD is the phenotype matrix
#  # bins is the previously calculated MDTS bins
#  # rl is the sequencing read length
#  counts = calcCounts(pD, bins, rl=100)

## ---- message=FALSE, warning=F------------------------------------------------
load(system.file("extdata", 'bins.RData', package = "MDTS"))
load(system.file("extdata", 'counts.RData', package = "MDTS"))
load(system.file("extdata", 'pD.RData', package = "MDTS"))

## -----------------------------------------------------------------------------
bins

## -----------------------------------------------------------------------------
head(counts)

## ---- warning=F---------------------------------------------------------------
# counts is the raw read depth of [MDTS bins x samples]
# bins is the previously calculated MDTS bins
mCounts <- normalizeCounts(counts, bins)

## ---- warning=F---------------------------------------------------------------
# mCounts is the normalized read depth of [MDTS bins x samples]
# bins is the previously calculated MDTS bins
# pD is the phenotype matrix
md <- calcMD(mCounts, pD)

## ---- warning=FALSE, message=FALSE, warning=F---------------------------------
# md is the Minimum Distance of [MDTS bins x trio]
# bins is the previously calculated MDTS bins
# mCounts is the normalized read depth of [MDTS bins x samples]
cbs <- segmentMD(md=md, bins=bins)
denovo <- denovoDeletions(cbs, mCounts, bins)

## -----------------------------------------------------------------------------
denovo

## -----------------------------------------------------------------------------
sessionInfo()