## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----"install", eval = FALSE-------------------------------------------------- # if (!requireNamespace("BiocManager", quietly = TRUE)) { # install.packages("BiocManager") # } # BiocManager::install("cfTools") ## ----'install_dev', eval = FALSE---------------------------------------------- # BiocManager::install("jasminezhoulab/cfTools") ## ----demo--------------------------------------------------------------------- library(cfTools) library(utils) demo.dir <- system.file("data", package="cfTools") ## ----------------------------------------------------------------------------- PEReads <- file.path(demo.dir, "demo.sorted.bed.txt.gz") head(read.table(PEReads, header=FALSE), 2) ## ----------------------------------------------------------------------------- fragInfo <- MergePEReads(PEReads) head(fragInfo, 2) ## ----------------------------------------------------------------------------- CpG_OT <- file.path(demo.dir, "CpG_OT_demo.txt.gz") CpG_OB <- file.path(demo.dir, "CpG_OB_demo.txt.gz") head(read.table(CpG_OT, header=FALSE), 2) head(read.table(CpG_OB, header=FALSE), 2) ## ----------------------------------------------------------------------------- methInfo <- MergeCpGs(CpG_OT, CpG_OB) head(methInfo, 2) ## ----------------------------------------------------------------------------- fragMeth <- GenerateFragMeth(fragInfo, methInfo) head(fragMeth, 2) ## ----------------------------------------------------------------------------- methLevel <- read.table(file.path(demo.dir, "beta_matrix.txt.gz"), row.names=1, header = TRUE) sampleTypes <- read.table(file.path(demo.dir, "sample_type.txt.gz"), row.names=1, header = TRUE)$sampleType markerNames <- read.table(file.path(demo.dir, "marker_index.txt.gz"), row.names=1, header = TRUE)$markerIndex print(methLevel) print(sampleTypes) print(markerNames) ## ----------------------------------------------------------------------------- markerParam <- GenerateMarkerParam(methLevel, sampleTypes, markerNames) print(markerParam) ## ----message=FALSE------------------------------------------------------------ library(GenomicRanges) # a BED file of fragment-level methylation information frag_bed <- read.csv(file.path(demo.dir, "demo.fragment_level.meth.bed.txt.gz"), header=TRUE, sep="\t") frag_meth.gr <- GRanges(seqnames=frag_bed$chr, ranges=IRanges(frag_bed$start, frag_bed$end), strand=frag_bed$strand, methState=as.character(frag_bed$methState)) # a BED file of genomic regions of markers markers_bed <- read.csv(file.path(demo.dir, "markers.bed.txt.gz"), header=TRUE, sep="\t") markers.gr <- GRanges(seqnames=markers_bed$chr, ranges=IRanges(markers_bed$start, markers_bed$end), markerName=markers_bed$markerName) head(frag_meth.gr, 2) head(markers.gr, 2) ## ----------------------------------------------------------------------------- ranges <- subsetByOverlaps(frag_meth.gr, markers.gr, ignore.strand=TRUE) hits <- findOverlaps(frag_meth.gr, markers.gr,ignore.strand=TRUE) idx <- subjectHits(hits) values <- DataFrame(markerName=markers.gr$markerName[idx]) mcols(ranges) <- c(mcols(ranges), values) marker.methState <- as.data.frame(cbind(ranges$markerName, ranges$methState)) colnames(marker.methState) <- c("markerName", "methState") head(marker.methState, 4) ## ----------------------------------------------------------------------------- fragMethFile <- file.path(demo.dir, "CancerDetector.reads.txt.gz") markerParamFile <- file.path(demo.dir, "CancerDetector.markers.txt.gz") head(read.csv(fragMethFile, sep = "\t", colClasses = "character"), 4) head(read.csv(markerParamFile, sep = "\t"), 4) ## ----------------------------------------------------------------------------- CancerDetector(fragMethFile, markerParamFile, lambda=0.5, id="test") ## ----------------------------------------------------------------------------- fragMethFile2 <- file.path(demo.dir, "cfDeconvolve.reads.txt.gz") markerParamFile2 <- file.path(demo.dir, "cfDeconvolve.markers.txt.gz") head(read.csv(fragMethFile2, header=TRUE, sep="\t", colClasses = "character"), 4) head(read.csv(markerParamFile2, header=TRUE, sep="\t", colClasses = "character"), 4) ## ----------------------------------------------------------------------------- numTissues <- 7 emAlgorithmType <- "em.global.unknown" likelihoodRatioThreshold <- 2 emMaxIterations <- 100 randomSeed <- 0 id <- "test" ## ----message=TRUE------------------------------------------------------------- tissueFraction <- cfDeconvolve(fragMethFile2, markerParamFile2, numTissues, emAlgorithmType, likelihoodRatioThreshold, emMaxIterations, randomSeed, id) tissueFraction ## ----------------------------------------------------------------------------- fragMethInfo <- file.path(demo.dir, "cfsort_reads.txt.gz") head(read.csv(fragMethInfo, header=TRUE, sep="\t", colClasses = "character"), 4) ## ----message=FALSE------------------------------------------------------------ tissueFraction2 <- cfSort(fragMethInfo, id="demo") tissueFraction2 ## ----sessionInfo, echo=FALSE-------------------------------------------------- sessionInfo()