## ----消息= false，警告= false ---------------------------------------------------------------------------------库（Chromvar）库（MotifMatchr）库（矩阵）库（摘要experiment）库（bioCparallel）set.seed（2017）## --------------------------------------------------------------------------------------------------------------------------------------------------------------注册（MulticoreParam（8））## -------------------------------------------------------------------------------------------------------------------------- register(MulticoreParam(8,progressbar = true））## --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------寄存器（雪帕拉姆（工人= 1，type =“ sock”））＃＃---------------------------------------------------------------------------------------------------------- register(SerialParam()) ## --------------------------------------------------------------------------------------------------------------- peakfile <- system.file("extdata/test_bed.txt", package = "chromVAR") peaks <- getPeaks(peakfile, sort_peaks = TRUE) ## --------------------------------------------------------------------------------------------------------------- bamfile <- system.file("extdata/test_RG.bam",package =“ chromvar”）fragment_counts < - getCounts（bamfile，peaks，peaked = true，by_rg = true，format =“ bam”，coldata = dataframe（cellType =“ gm”）## -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------数据（example_counts，package =“ chromvar”）head（example_counts）## ----消息= false --------------- - - - - - - - - - - - - - - - - - - - - - - - - 图书馆(BSgenome.Hsapiens.UCSC.hg19) example_counts <- addGCBias(example_counts, genome = BSgenome.Hsapiens.UCSC.hg19) head(rowData(example_counts)) ## ----------------------------------------------------------------------------- #find indices of samples to keep counts_filtered <- filterSamples(example_counts, min_depth = 1500, min_in_peaks = 0.15, shiny = FALSE) ## ----filter_plot, fig.width = 6, fig.height = 6------------------------------- #find indices of samples to keep filtering_plot <- filterSamplesPlot(example_counts, min_depth = 1500, min_in_peaks = 0.15, use_plotly = FALSE) filtering_plot ## ----------------------------------------------------------------------------- ix <- filterSamples(example_counts, ix_return = TRUE, shiny = FALSE) ## ----------------------------------------------------------------------------- counts_filtered <- filterPeaks(counts_filtered, non_overlapping = TRUE) ## ----------------------------------------------------------------------------- motifs <- getJasparMotifs() ## ----------------------------------------------------------------------------- yeast_motifs <- getJasparMotifs(species = "Saccharomyces cerevisiae") ## ----------------------------------------------------------------------------- library(motifmatchr) motif_ix <- matchMotifs(motifs, counts_filtered, genome = BSgenome.Hsapiens.UCSC.hg19) ## ----------------------------------------------------------------------------- kmer_ix <- matchKmers(6, counts_filtered, genome = BSgenome.Hsapiens.UCSC.hg19) ## ----------------------------------------------------------------------------- dev <- computeDeviations(object = counts_filtered, annotations = motif_ix) ## ----------------------------------------------------------------------------- bg <- getBackgroundPeaks(object = counts_filtered) ## ----------------------------------------------------------------------------- dev <- computeDeviations(object = counts_filtered, annotations = motif_ix, background_peaks = bg) ## ----variability, fig.width = 6, fig.height = 6------------------------------- variability <- computeVariability(dev) plotVariability(variability, use_plotly = FALSE) ## ----------------------------------------------------------------------------- tsne_results <- deviationsTsne(dev, threshold = 1.5, perplexity = 10) ## ----------------------------------------------------------------------------- tsne_plots <- plotDeviationsTsne(dev, tsne_results, annotation_name = "TEAD3", sample_column = "Cell_Type", shiny = FALSE) tsne_plots[[1]] tsne_plots[[2]] ## ----------------------------------------------------------------------------- Sys.Date() ## ----------------------------------------------------------------------------- sessionInfo()