# colorspace_1.2-6 KernSmooth_2.I can never seem to get exactly what I want from an R text editor. # htmltools_0.2.6 GenomicAlignments_1.4.2 # loaded via a namespace (and not attached): # stats4 parallel grid stats graphics grDevices utils Names(sml) = sampleInfo$sampleNameĪrithmetic, indicator and logic operations as well as subsetting work on score matricesĪrithmetic, indicator and logic operations work on ScoreMatrix, ScoreMatrixBin and ScoreMatrixListĪrith: “+”, “-”, “*”, “ ”, “%%”, “%/%”, “/” Package='genomationData'),header=TRUE, sep='\t') SampleInfo = read.table(system.file('extdata/SamplesInfo.txt', # descriptions of file that contain info. sml = ScoreMatrixList(bam.files, ctcf.peaks, bin.num=50, type='bam', cores=2) That indicates number of cores to be used at the same time (by using parallel:mclapply). ScoreMatrixList was improved by adding new argument cores We use ScoreMatrixList function to extract coverage values of all transcription factorsĪround ChIP-seq peaks. Parallelizing data processing in ScoreMatrixList ''))Ĭtcf.peaks = ctcf.peaksĬtcf.peaks = resize(ctcf.peaks, width=1000, fix='center') library(GenomicRanges)Ĭtcf.peaks = readBroadPeak(file.path(genomationDataPath, UCSC header is detected (and first track). This is achived by using readr::read_delim function to read genomic filesĪdditionally if skip=“auto” argument is provided in readGeneric_or track.line=“auto” in other functions GenomationDataPath = system.file('extdata',package='genomationData')īam.files = list.files(genomationDataPath, full.names=TRUE, pattern='bam$')īam.files = bam.filesĪccelerate functions responsible for reading genomic files Mates from readsĪre treated as fragments (they are stitched together). Genomation can work with paired-end BAM files. Install_github("BIMSBbioinfo/genomation",build_vignettes=FALSE)Įxtending genomation to work with paired-end BAM files Recently we added new features to genomation and here we present them on example ofīinding profiles of 6 transcription factors around the CTCF binding sites derived from ChIP-seq.Īll new functionalities are available in the latest version of genomation that can be found on RNA-seq, bisulfite sequencing or chromatin-immunoprecipitation followed by sequencing It contains a collection of tools for visualizing and analyzing genome-wide data sets, Genomation is an R package to summarize, annotateĪnd visualize genomic intervals. Integration with Travis CI for auto-testing.Calculating scores that correspond to k-mer or PWM matrix occurence: patternMatrix function.Plotting dispersion around central lines in line plots: dispersion in plotMeta.Smoothing central tendency: smoothfun in plotMeta.Central tendencies in line plots: centralTend in plotMeta.Defining which matrices are used for clustering: “clust.matrix” in multiHeatMatrix.New clustering possibilities in heatmaps: “clustfun” argument in multiHeatMatrix.Improvements and new arguments in visualization functions.Arithmetic, indicator and logic operations as well as subsetting work on ScoreMatrix objects.Parallelizing data processing in ScoreMatrixList.
Accelerate functions responsible for reading genomic files.Extending genomation to work with paired-end BAM files.
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