Title: | Differential Enrichment Scan 2 |
---|---|
Description: | Integrated peak and differential caller, specifically designed for broad epigenomic signals. |
Authors: | Dario Righelli [aut, cre], John Koberstein [aut], Bruce Gomes [aut], Nancy Zhang [aut], Claudia Angelini [aut], Lucia Peixoto [aut], Davide Risso [aut] |
Maintainer: | Dario Righelli <[email protected]> |
License: | Artistic-2.0 |
Version: | 1.27.0 |
Built: | 2024-11-29 05:27:14 UTC |
Source: | https://github.com/bioc/DEScan2 |
this function computes the coverage over a binned chromosome, starting from a per base computed coverage.
binnedCoverage( bins, numvar, mcolname, covMethod = c("max", "mean", "sum", "min"), roundingMethod = c("none", "floor", "ceiling", "round") )
binnedCoverage( bins, numvar, mcolname, covMethod = c("max", "mean", "sum", "min"), roundingMethod = c("none", "floor", "ceiling", "round") )
bins |
a GRanges object representing a chromosome binned. |
numvar |
an RleList representing the per base coverage over the chr. |
mcolname |
the name of column where the sum have to be stored. |
covMethod |
a method to apply for the computing of the coverate it can be one of "max", "mean", "sum", "min". ("max" is default) |
roundingMethod |
a method to apply to round the computations it can be one of "none", "floor", "ceiling", "round". It's useful only when using covMethod="mean". ("none" is default) |
the bins GRanges with the mcolname attached
## dividing one chromosome in bins of 50 bp each seqinfo <- GenomeInfoDb::Seqinfo(genome="mm9") bins <- GenomicRanges::tileGenome( seqlengths=GenomeInfoDb::seqlengths(seqinfo)[1], tilewidth=50, cut.last.tile.in.chrom=TRUE) gr <- GenomicRanges::GRanges(seqnames = S4Vectors::Rle("chr1", 100), ranges=IRanges::IRanges(start = seq(from=10, to=1000, by=10), end=seq(from=20, to=1010, by = 10))) cov <- GenomicRanges::coverage(x=gr) (binnedMaxCovGR <- binnedCoverage(bins, cov, "binned_cov")) (binnedMeanCovGR <- binnedCoverage(bins, cov, "binned_cov", covMethod="mean", roundingMethod="floor")) (binnedSumCovGR <- binnedCoverage(bins, cov, "binned_cov", covMethod="sum"))
## dividing one chromosome in bins of 50 bp each seqinfo <- GenomeInfoDb::Seqinfo(genome="mm9") bins <- GenomicRanges::tileGenome( seqlengths=GenomeInfoDb::seqlengths(seqinfo)[1], tilewidth=50, cut.last.tile.in.chrom=TRUE) gr <- GenomicRanges::GRanges(seqnames = S4Vectors::Rle("chr1", 100), ranges=IRanges::IRanges(start = seq(from=10, to=1000, by=10), end=seq(from=20, to=1010, by = 10))) cov <- GenomicRanges::coverage(x=gr) (binnedMaxCovGR <- binnedCoverage(bins, cov, "binned_cov")) (binnedMeanCovGR <- binnedCoverage(bins, cov, "binned_cov", covMethod="mean", roundingMethod="floor")) (binnedSumCovGR <- binnedCoverage(bins, cov, "binned_cov", covMethod="sum"))
Computes Z-Scores returning the z matrix.
computeZ( lambdaChrRleList, runWinRleList, chrLength, minCount = 0.1, binSize = 50, verbose = FALSE )
computeZ( lambdaChrRleList, runWinRleList, chrLength, minCount = 0.1, binSize = 50, verbose = FALSE )
lambdaChrRleList |
an RleList of lambda values computed by computeLambdaOnChr function each element of the list is an Rle representing the lambda for the moving window in the list position. |
runWinRleList |
an RleList of coverage values computed. by computeCoverageMovingWindowOnChr function each element of the list is an Rle representing the coverage for the moving window in the list position. |
chrLength |
the length of the chr in analysis. |
minCount |
A small constant (usually no larger than one) to be added to the counts prior to the log transformation to avoid problems with log(0). |
binSize |
the size of the bin. |
verbose |
verbose output. |
z a matrix of z scores for each window (column) and bin (row). where the rownames represent the starting base of each bin.
Constructs a GRanges object from a bam/bed/bed.zip file in a consistent way.
constructBedRanges( filename, filetype = c("bam", "bed", "bed.zip", "narrow", "broad"), genomeName = NULL, onlyStdChrs = FALSE, arePeaks = FALSE, verbose = FALSE )
constructBedRanges( filename, filetype = c("bam", "bed", "bed.zip", "narrow", "broad"), genomeName = NULL, onlyStdChrs = FALSE, arePeaks = FALSE, verbose = FALSE )
filename |
the complete file path of a bam?bed file. |
filetype |
the file type bam/bed/bed.zip/narrow/broad. |
genomeName |
the name of the genome used to map the reads (i.e. "mm9"). N.B. if NOT NULL the GRanges Seqinfo will be forced to genomeName Seqinfo (needs Internet access, but strongly suggested!) |
onlyStdChrs |
flag to keep only standard chromosome. |
arePeaks |
flag indicating if the file contains peaks. |
verbose |
flag to obtain verbose output. |
a GRanges object.
files <- list.files(system.file("extdata/bam/", package="DEScan2"), pattern="bam$", full.names=TRUE) bgr <- constructBedRanges(files[1], filetype="bam", genomeName="mm9", onlyStdChrs=TRUE) bgr
files <- list.files(system.file("extdata/bam/", package="DEScan2"), pattern="bam$", full.names=TRUE) bgr <- constructBedRanges(files[1], filetype="bam", genomeName="mm9", onlyStdChrs=TRUE) bgr
count reads falling within the final regions.
countFinalRegions( regionsGRanges, readsFilePath = NULL, fileType = c("bam", "bed"), minCarriers = 2, genomeName = NULL, onlyStdChrs = FALSE, carrierscolname = "k-carriers", ignStrandSO = TRUE, modeSO = "Union", saveFlag = FALSE, savePath = "finalRegions", verbose = TRUE )
countFinalRegions( regionsGRanges, readsFilePath = NULL, fileType = c("bam", "bed"), minCarriers = 2, genomeName = NULL, onlyStdChrs = FALSE, carrierscolname = "k-carriers", ignStrandSO = TRUE, modeSO = "Union", saveFlag = FALSE, savePath = "finalRegions", verbose = TRUE )
regionsGRanges |
a GRanges objects representing the peaks to compute the coverage, with a "k-carriers" mcols. (tipically generated by finalRegions function). |
readsFilePath |
the filepath of bam or bed files necessary to compute the coverage. |
fileType |
the file type of the input files. |
minCarriers |
minimum number of carriers (samples). |
genomeName |
code name of the genome of reads files (i.e. "mm9"). |
onlyStdChrs |
a flag indicating if to keep only the standard chromosomes |
carrierscolname |
character describing the name of the column within the carriers number (default is "k-carriers"). |
ignStrandSO |
a flag indicating if to ignore the reads strand. (see GenomicAlignments::summarizeOverlaps). |
modeSO |
the mode to use, default is "Union". (see GenomicAlignments::summarizeOverlaps). |
saveFlag |
a flag indicating if to save the results. |
savePath |
the path where to store the results. |
verbose |
verbose output. |
A SummarizedExperiment object containing as assays the read counts matrix with regions as rows and samples as columns, and as rowRanges the GRanges object representing the peaks used as rows in the matrix.
filename <- system.file("extdata/regions/regions.rds", package="DEScan2") regionsGR <- readRDS(file=filename) reads.path <- system.file("extdata/bam", package="DEScan2") finalRegionsSE <- countFinalRegions(regionsGRanges=regionsGR, readsFilePath=reads.path, fileType="bam", minCarriers=1, genomeName="mm9", onlyStdChrs=TRUE, ignStrandSO=TRUE, saveFlag=FALSE, verbose=TRUE) library("SummarizedExperiment") assay(finalRegionsSE) ## matrix of counts rowRanges(finalRegionsSE) ## the GRanges of the input regions
filename <- system.file("extdata/regions/regions.rds", package="DEScan2") regionsGR <- readRDS(file=filename) reads.path <- system.file("extdata/bam", package="DEScan2") finalRegionsSE <- countFinalRegions(regionsGRanges=regionsGR, readsFilePath=reads.path, fileType="bam", minCarriers=1, genomeName="mm9", onlyStdChrs=TRUE, ignStrandSO=TRUE, saveFlag=FALSE, verbose=TRUE) library("SummarizedExperiment") assay(finalRegionsSE) ## matrix of counts rowRanges(finalRegionsSE) ## the GRanges of the input regions
a simplified wrapper function to create a GRanges object.
createGranges(chrSeqInfo, starts, widths, mcolname = NULL, mcolvalues = NULL)
createGranges(chrSeqInfo, starts, widths, mcolname = NULL, mcolvalues = NULL)
chrSeqInfo |
a seqinfo object. |
starts |
the start ranges. |
widths |
the width of each range. |
mcolname |
the name for the mcol attribute. |
mcolvalues |
the values for the mcol attribute. |
a GRanges object.
chrSeqInfo <- GenomeInfoDb::Seqinfo(genome="mm9")["chr1"] starts=sample(seq_len(100), 10) widths=starts+10; mcolname <- "z-score"; mcolvalues <- sample(seq_len(100), 10) chrGR <- createGranges(chrSeqInfo=chrSeqInfo, starts=starts, widths=widths, mcolname=mcolname, mcolvalues=mcolvalues)
chrSeqInfo <- GenomeInfoDb::Seqinfo(genome="mm9")["chr1"] starts=sample(seq_len(100), 10) widths=starts+10; mcolname <- "z-score"; mcolvalues <- sample(seq_len(100), 10) chrGR <- createGranges(chrSeqInfo=chrSeqInfo, starts=starts, widths=widths, mcolname=mcolname, mcolvalues=mcolvalues)
takes in input a GRanges object, producing a LIST of GRanges, one for each chromosome.
cutGRangesPerChromosome(GRanges)
cutGRangesPerChromosome(GRanges)
GRanges |
a GRanges object. |
a named list of GRanges, one for each chromosome.
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) (grchrlist <- cutGRangesPerChromosome(gr))
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) (grchrlist <- cutGRangesPerChromosome(gr))
integrated peak and differential caller, specifically designed for broad epigenomic signals.
some authors
taken in input a grangeslist of samples, generate a list of samples where each element has a GRangesList each element of the GRangesList represents a single chromosome.
divideEachSampleByChromosomes(samplesGRangesList)
divideEachSampleByChromosomes(samplesGRangesList)
samplesGRangesList |
a GRangesList of samples. |
list of samples where each element is a list of chromosomes and each of these elements is a GRanges.
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) gr2 <- GRanges( seqnames=Rle(c("chr1", "chr4", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr4=12, chr3=13)) sgrl <- GRangesList(gr1, gr2) names(sgrl) <- c("samp1", "samp2") (sampChrGrl <- divideEachSampleByChromosomes(sgrl))
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) gr2 <- GRanges( seqnames=Rle(c("chr1", "chr4", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr4=12, chr3=13)) sgrl <- GRangesList(gr1, gr2) names(sgrl) <- c("samp1", "samp2") (sampChrGrl <- divideEachSampleByChromosomes(sgrl))
Align peaks to form common regions then filter regions for presence in multiple replicates taking in input a GRangesList where each element is a sample of called peaks.
finalRegions( peakSamplesGRangesList, zThreshold = 20, minCarriers = 2, saveFlag = TRUE, outputFolder = "overlappedPeaks", verbose = FALSE, scorecolname = "z-score", coverageFlag = FALSE, BPPARAM = BiocParallel::bpparam() )
finalRegions( peakSamplesGRangesList, zThreshold = 20, minCarriers = 2, saveFlag = TRUE, outputFolder = "overlappedPeaks", verbose = FALSE, scorecolname = "z-score", coverageFlag = FALSE, BPPARAM = BiocParallel::bpparam() )
peakSamplesGRangesList |
named GRangesList where each element is a sample of called peaks. A score mcols values is needed for each GRanges. The scorecolname param can be used as reference name for the score. (tipically returned by findPeaks function). |
zThreshold |
a minimum threshold for the z score. All peaks lesser than this value will be ignored. |
minCarriers |
a threshold of minimum samples (carriers) for overlapped regions. |
saveFlag |
a flag for saving results in a tsv file. |
outputFolder |
the directory name to store the bed file. |
verbose |
verbose output. |
scorecolname |
character describing the name of the column within the peaks score. |
coverageFlag |
boolean indicating if to compute the scores in a coverage mode (sum of the reads of merged peak) or in a score mode (a normalized score across the merged peaks) |
BPPARAM |
object of class |
a GRanges of selected overlapping peaks with z-score, n-peaks, k-carriers as mcols object.
peak.path <- system.file("extdata/peaks/RData/peaksGRL_all_files.rds", package="DEScan2") grl <- readRDS(peak.path) grl regionsGR <- finalRegions(peakSamplesGRangesList=grl, zThreshold=1, minCarriers=3, saveFlag=FALSE, verbose=TRUE)
peak.path <- system.file("extdata/peaks/RData/peaksGRL_all_files.rds", package="DEScan2") grl <- readRDS(peak.path) grl regionsGR <- finalRegions(peakSamplesGRangesList=grl, zThreshold=1, minCarriers=3, saveFlag=FALSE, verbose=TRUE)
given in input a GRangeList where each element is a sample computes the coverage extending a both direction window of prefixed length.
findOverlapsOverSamples( samplePeaksGRangelist, extendRegions = 200, minOverlap = 0L, maxGap = -1L, zThresh = 10, verbose = FALSE, scorecolname = "z-score", coverageFlag = FALSE )
findOverlapsOverSamples( samplePeaksGRangelist, extendRegions = 200, minOverlap = 0L, maxGap = -1L, zThresh = 10, verbose = FALSE, scorecolname = "z-score", coverageFlag = FALSE )
samplePeaksGRangelist |
given a granges list of samples finds the overlapping regions between them. |
extendRegions |
the number of bases to extend each region at its start and end. |
minOverlap |
the minimum overlap each peak needs to have. (see ChipPeakAnno::findOverlapsOfPeaks) |
maxGap |
the maximum gap admissible between the peaks. (see ChipPeakAnno::findOverlapsOfPeaks) |
zThresh |
a threshold value on z-score/scorecolname |
verbose |
verbose flag |
scorecolname |
character describing the name of the column within the peaks score. |
coverageFlag |
boolean indicating if to compute the scores in a coverage mode (sum of the reads of merged peak) or in a score mode (a normalized score across the merged peaks) |
a GRanges of peaks overlapped and unique between samples.
(peaks.file <- system.file("extdata/peaks/RData/peaksGRL_all_files.rds", package="DEScan2")) peaksGRLFiles <- readRDS(peaks.file) (overlPeaks <- findOverlapsOverSamples(peaksGRLFiles))
(peaks.file <- system.file("extdata/peaks/RData/peaksGRL_all_files.rds", package="DEScan2")) peaksGRLFiles <- readRDS(peaks.file) (overlPeaks <- findOverlapsOverSamples(peaksGRLFiles))
This function calls peaks from bed or bam inputs using a variable window scan with a poisson model using the surrounding maxCompWinWidth (10kb) as background.
findPeaks( files, filetype = c("bam", "bed"), genomeName = NULL, binSize = 50, minWin = 50, maxWin = 1000, zthresh = 10, minCount = 0.1, minCompWinWidth = 5000, maxCompWinWidth = 10000, outputFolder = "Peaks", save = TRUE, force = TRUE, verbose = FALSE, sigwin = 10, onlyStdChrs = TRUE, chr = NULL, BPPARAM = BiocParallel::bpparam() )
findPeaks( files, filetype = c("bam", "bed"), genomeName = NULL, binSize = 50, minWin = 50, maxWin = 1000, zthresh = 10, minCount = 0.1, minCompWinWidth = 5000, maxCompWinWidth = 10000, outputFolder = "Peaks", save = TRUE, force = TRUE, verbose = FALSE, sigwin = 10, onlyStdChrs = TRUE, chr = NULL, BPPARAM = BiocParallel::bpparam() )
files |
Character vector containing paths of files to be analyzed. |
filetype |
Character, either "bam" or "bed" indicating format of input file. |
genomeName |
the code of the genome to use as reference for the input files. (cfr. constructBedRanges function parameters) |
binSize |
Integer size in bases of the minimum window for scanning, 50 is the default. |
minWin |
Integer indicating the minimum window size in bases notation. |
maxWin |
Integer indicating the maximum window size in bases notation. |
zthresh |
Cuttoff value for z-scores. Only windows with greater z-scores will be kept, default is 10. |
minCount |
A small constant (usually no larger than one) to be added to the counts prior to the log transformation to avoid problems with log(0). |
minCompWinWidth |
minimum bases width of a comparing window for Z-score. |
maxCompWinWidth |
maximum bases width of a comparing window for Z-score. |
outputFolder |
A string, Name of the folder to save the Peaks (optional) if the directory doesn't exist, it will be created. (Default is "Peaks") |
save |
Boolean, if TRUE files will be saved in a "./Peaks/chr*" directory created (if not already present) in the current working directory. |
force |
a boolean flag indicating if to force output overwriting. |
verbose |
if to show additional messages |
sigwin |
an integer value used to compute the length of the signal of a peak (default value is 10). |
onlyStdChrs |
a flag to work only with standard chromosomes. (cfr. constructBedRanges function parameters). |
chr |
if not NULL, a character like "chr#" indicating the chromosomes to use. |
BPPARAM |
object of class |
A GRangesList where each element is a sample. Each GRanges represents the founded peaks and attached the z-score of the peak as mcols.
bam.files <- list.files(system.file("extdata/bam", package = "DEScan2"), full.names = TRUE) peaks <- findPeaks(files=bam.files[1], filetype="bam", genomeName="mm9", binSize=50, minWin=50, maxWin=1000, zthresh=5, minCount=0.1, sigwin=10, minCompWinWidth=5000, maxCompWinWidth=10000, save=FALSE, onlyStdChrs=TRUE, chr=NULL, verbose=FALSE) head(peaks)
bam.files <- list.files(system.file("extdata/bam", package = "DEScan2"), full.names = TRUE) peaks <- findPeaks(files=bam.files[1], filetype="bam", genomeName="mm9", binSize=50, minWin=50, maxWin=1000, zthresh=5, minCount=0.1, sigwin=10, minCompWinWidth=5000, maxCompWinWidth=10000, save=FALSE, onlyStdChrs=TRUE, chr=NULL, verbose=FALSE) head(peaks)
converts a GRangesList orgnized per samples to a GRangesList organized per Chromosomes where each element is a GRangesList of samples.
fromSamplesToChrsGRangesList(samplesGRangesList)
fromSamplesToChrsGRangesList(samplesGRangesList)
samplesGRangesList |
a GRangesList of samples. Tipically generaed by findPeaks function. |
A GRangesList of chromosomes where each element is a GRanges list of samples.
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) gr2 <- GRanges( seqnames=Rle(c("chr1", "chr4", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr4=12, chr3=13)) sgrl <- GRangesList(gr1, gr2) names(sgrl) <- c("samp1", "samp2") (chrGrlSampGr <- fromSamplesToChrsGRangesList(sgrl))
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) gr2 <- GRanges( seqnames=Rle(c("chr1", "chr4", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr4=12, chr3=13)) sgrl <- GRangesList(gr1, gr2) names(sgrl) <- c("samp1", "samp2") (chrGrlSampGr <- fromSamplesToChrsGRangesList(sgrl))
subselect a list of GRanges created with cutGRangesPerChromosome returning only the relevant chromosomes GRanges.
keepRelevantChrs(chrGRangesList, chr = NULL)
keepRelevantChrs(chrGRangesList, chr = NULL)
chrGRangesList |
where each element is a chromosome, tipically created with cutGRangesPerChromosome. |
chr |
a character vector of chromosomes names of the form "chr#". |
the input chrGRangesList with only the relevat chromosomes.
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) grlc <- cutGRangesPerChromosome(gr1) (grlChr <- keepRelevantChrs(grlc, c("chr1", "chr3")))
library("GenomicRanges") gr1 <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) grlc <- cutGRangesPerChromosome(gr1) (grlChr <- keepRelevantChrs(grlc, c("chr1", "chr3")))
read a bam file into a bed like format. forcing UCSC format for chromosomes names.
readBamAsBed(file)
readBamAsBed(file)
file |
Character indicating path to bam file. |
GRanges object.
files <- list.files(system.file("extdata/bam", package="DEScan2"), full.names=TRUE) gr <- readBamAsBed(files[1])
files <- list.files(system.file("extdata/bam", package="DEScan2"), full.names=TRUE) gr <- readBamAsBed(files[1])
read a bed file into a GenomicRanges like format. forcing UCSC format for chromosomes names.
readBedFile(filename, arePeaks = FALSE)
readBedFile(filename, arePeaks = FALSE)
filename |
the bed filename. |
arePeaks |
a flag indicating if the the bed file represents peaks. |
GRanges object
bedFile <- list.files(system.file("extdata/bed",package="DEScan2"), full.names=TRUE) gr <- readBedFile(bedFile)
bedFile <- list.files(system.file("extdata/bed",package="DEScan2"), full.names=TRUE) gr <- readBedFile(bedFile)
Takes in input the path of bam/bed files to process and stores them in a GRangesList object, named with filePath/filenames. (for lazy people)
readFilesAsGRangesList( filePath, fileType = c("bam", "bed", "bed.zip", "narrow", "broad"), genomeName = NULL, onlyStdChrs = TRUE, arePeaks = TRUE, verbose = TRUE )
readFilesAsGRangesList( filePath, fileType = c("bam", "bed", "bed.zip", "narrow", "broad"), genomeName = NULL, onlyStdChrs = TRUE, arePeaks = TRUE, verbose = TRUE )
filePath |
the path of input files. |
fileType |
the type of the files (bam/bed/bed.zip/narrow/broad). |
genomeName |
the genome code to associate to the files. (recommended) (i.e. "mm9", "hg17") |
onlyStdChrs |
a flag to keep only standard chromosomes. |
arePeaks |
a flag indicating if the files contain peaks. |
verbose |
verbose output flag. |
a GRangesList object
files.path <- system.file("extdata/bam", package="DEScan2") grl <- readFilesAsGRangesList(filePath=files.path, fileType="bam", genomeName="mm9", onlyStdChrs=TRUE, verbose=TRUE) class(grl) names(grl) grl
files.path <- system.file("extdata/bam", package="DEScan2") grl <- readFilesAsGRangesList(filePath=files.path, fileType="bam", genomeName="mm9", onlyStdChrs=TRUE, verbose=TRUE) class(grl) names(grl) grl
a wrapper to create a RleMatrix from a RleList object.
RleListToRleMatrix(RleList, dimnames = NULL)
RleListToRleMatrix(RleList, dimnames = NULL)
RleList |
an RleList object with all elements of the same length. |
dimnames |
the names for dimensions of RleMatrix (see DelayedArray pkg). |
a RleMatrix from DelayedArray package.
library("DelayedArray") lengths <- c(3, 1, 2) values <- c(15, 5, 20) el1 <- S4Vectors::Rle(values=values, lengths=lengths) el2 <- S4Vectors::Rle(values=sort(values), lengths=lengths) rleList <- IRanges::RleList(el1, el2) names(rleList) <- c("one", "two") (rleMat <- RleListToRleMatrix(rleList))
library("DelayedArray") lengths <- c(3, 1, 2) values <- c(15, 5, 20) el1 <- S4Vectors::Rle(values=values, lengths=lengths) el2 <- S4Vectors::Rle(values=sort(values), lengths=lengths) rleList <- IRanges::RleList(el1, el2) names(rleList) <- c("one", "two") (rleMat <- RleListToRleMatrix(rleList))
save a GRanges object as bed file.
saveGRangesAsBed( GRanges, filepath = tempdir(), filename = tempfile(), force = FALSE, verbose = FALSE )
saveGRangesAsBed( GRanges, filepath = tempdir(), filename = tempfile(), force = FALSE, verbose = FALSE )
GRanges |
the GRanges object. |
filepath |
the path to store the files.@ |
filename |
the name to give to the files. |
force |
force overwriting. |
verbose |
verbose output flag. |
none
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) saveGRangesAsBed(GRanges=gr, filepath=tempdir(), filename=tempfile(), verbose=TRUE)
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) saveGRangesAsBed(GRanges=gr, filepath=tempdir(), filename=tempfile(), verbose=TRUE)
save a GRanges object as tsv file.
saveGRangesAsTsv( GRanges, filepath = tempdir(), filename = tempfile(), col.names = NA, row.names = TRUE, sep = "\t", force = FALSE, verbose = FALSE )
saveGRangesAsTsv( GRanges, filepath = tempdir(), filename = tempfile(), col.names = NA, row.names = TRUE, sep = "\t", force = FALSE, verbose = FALSE )
GRanges |
the GRanges object. |
filepath |
the path to store the files. |
filename |
the name to give to the files. |
col.names |
a logical value indicating whether the column names are to be written in the file, or a character vector indicating the column names, or NA for writing column names for writing a TAB for the column name of the row names, default is NA (see write.table). |
row.names |
a logical value indicating whether the row names are to be written in the file, or a character vector indicating the row names (see write.table). |
sep |
the column separator character (default is \"\t\"). |
force |
force overwriting. |
verbose |
verbose output flag. |
none
gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) saveGRangesAsTsv(gr, verbose=TRUE)
gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) saveGRangesAsTsv(gr, verbose=TRUE)
setGRGenomeInfo given a genome code (i.e. "mm9","mm10","hg19","hg38") retrieve the SeqInfo of that genome and assigns it to the input GRanges. Finally filters out those Infos not necessary to the GRanges.
setGRGenomeInfo(GRanges, genomeName = NULL, verbose = FALSE)
setGRGenomeInfo(GRanges, genomeName = NULL, verbose = FALSE)
GRanges |
a GRanges object. |
genomeName |
a genome code (i.e. "mm9") |
verbose |
verbose output |
a GRanges object with the seqinfo of the genome code
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) mm9gr <- setGRGenomeInfo(GRanges=gr, genomeName="mm9", verbose=TRUE)
library("GenomicRanges") gr <- GRanges( seqnames=Rle(c("chr1", "chr2", "chr1", "chr3"), c(1, 3, 2, 4)), ranges=IRanges(1:10, end=10), strand=Rle(strand(c("-", "+", "*", "+", "-")), c(1, 2, 2, 3, 2)), seqlengths=c(chr1=11, chr2=12, chr3=13)) mm9gr <- setGRGenomeInfo(GRanges=gr, genomeName="mm9", verbose=TRUE)