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(转帖)-circos-circlize-4

(转帖)-circos-circlize-4

作者: 苏慕晨枫 | 来源:发表于2018-06-11 23:00 被阅读17次

    原文地址:https://mp.weixin.qq.com/s/AK3UICxBYTnG98jy_6q4gA

    我们首先看一下绘制点:

    par(mar = c(1, 1, 1, 1))

    set.seed(1)

    #起始角度90

    circos.par("track.height" = 0.1, start.degree = 90,gap.degree=270)

    #初始化(绘制第一染色体,表示仅有一个扇形)

    circos.initializeWithIdeogram(chromosome.index = "chr1", plotType = NULL)

    #构造数据框

    bed = generateRandomBed(nr = 300)

    #创建轨道,并在上面添加点

    circos.genomicTrackPlotRegion(bed, panel.fun = function(region, value, ...) {

    circos.genomicPoints(region, value, pch = 16, cex = 0.5, ...)

    })

    #继续构造数据集

    bed = generateRandomBed(nr = 300)

    #堆叠(类似与ggplot中的位置参数stack),点上加线

    circos.genomicTrackPlotRegion(bed, stack = TRUE,

    panel.fun = function(region, value, ...) {

    circos.genomicPoints(region, value, pch = 16, cex = 0.5, ...)

    #在当前数据框

    i = getI(...)

    cell.xlim = get.cell.meta.data("cell.xlim")

    circos.lines(cell.xlim, c(i, i), lty = 2, col = "#00000040")

    })

    #产生两个数据集

    bed1 = generateRandomBed(nr = 300)

    bed2 = generateRandomBed(nr = 300)

    #组合在一起

    bed_list = list(bed1, bed2)

    #两个数据集在同一个轨道上添加点(i=get(...)必须有)

    circos.genomicTrackPlotRegion(bed_list,

    panel.fun = function(region, value, ...) {

    cex = (value[[1]] - min(value[[1]]))/(max(value[[1]]) - min(value[[1]]))

    i = getI(...)

    circos.genomicPoints(region, value, cex = cex, pch = 16, col = i, ...)

    })

    #堆叠circos.genomicTrackPlotRegion(bed_list, stack = TRUE,

    panel.fun = function(region, value, ...) {

    cex = (value[[1]] - min(value[[1]]))/(max(value[[1]]) - min(value[[1]]))

    i = getI(...)

    circos.genomicPoints(region, value, cex = cex, pch = 16, col = i, ...)

    cell.xlim = get.cell.meta.data("cell.xlim")

    circos.lines(cell.xlim, c(i, i), lty = 2, col = "#00000040")

    })

    #构造数据集(多个变量)

    bed = generateRandomBed(nr = 300, nc = 4)

    circos.genomicTrackPlotRegion(bed,

    panel.fun = function(region, value, ...) {

    circos.genomicPoints(region, value, cex = 0.5, pch = 16, col = 1:4, ...)

    })

    bed = generateRandomBed(nr = 300, nc = 4)

    circos.genomicTrackPlotRegion(bed, stack = TRUE,

    panel.fun = function(region, value, ...) {

    cex = (value[[1]] - min(value[[1]]))/(max(value[[1]]) - min(value[[1]]))

    i = getI(...)

    circos.genomicPoints(region, value, cex = cex, pch = 16, col = i, ...)

    cell.xlim = get.cell.meta.data("cell.xlim")

    circos.lines(cell.xlim, c(i, i), lty = 2, col = "#00000040")

    })

    circos.clear()

    下面绘制线:

    par(mar = c(1, 1, 1, 1))

    circos.par("track.height" = 0.1, start.degree = 90, gap.degree = 270)

    circos.initializeWithIdeogram(chromosome.index = "chr1", plotType = NULL)

    bed = generateRandomBed(nr = 500)

    circos.genomicTrackPlotRegion(bed,

    panel.fun = function(region, value, ...) {

    circos.genomicLines(region, value, type = "l", ...)

    })

    bed1 = generateRandomBed(nr = 500)

    bed2 = generateRandomBed(nr = 500)

    bed_list = list(bed1, bed2)

    circos.genomicTrackPlotRegion(bed_list,

    panel.fun = function(region, value, ...) {

    i = getI(...)

    circos.genomicLines(region, value, col = i, ...)

    })

    circos.genomicTrackPlotRegion(bed_list, stack = TRUE,

    panel.fun = function(region, value, ...) {

    i = getI(...)

    circos.genomicLines(region, value, col = i, ...)

    })

    bed = generateRandomBed(nr = 500, nc = 4)

    circos.genomicTrackPlotRegion(bed,

    panel.fun = function(region, value, ...) {

    circos.genomicLines(region, value, col = 1:4, ...)

    })

    bed = generateRandomBed(nr = 500, nc = 4)

    circos.genomicTrackPlotRegion(bed, stack = TRUE,

    panel.fun = function(region, value, ...) {

    i = getI(...)

    circos.genomicLines(region, value, col = i, ...)

    })

    bed = generateRandomBed(nr = 200)

    circos.genomicTrackPlotRegion(bed,

    panel.fun = function(region, value, ...) {

    circos.genomicLines(region, value, type = "segment", lwd = 2,

    col = rand_color(nrow(region)), ...)

    })

    circos.clear()

    绘制矩形:

    par(mar = c(1, 1, 1, 1))

    circos.par("track.height" = 0.1, start.degree = 90,gap.degree = 270)

    circos.initializeWithIdeogram(chromosome.index = "chr1", plotType = NULL)

    f = colorRamp2(breaks = c(-1, 0, 1), colors = c("green", "black", "red"))

    bed = generateRandomBed(nr = 100, nc = 4)

    circos.genomicTrackPlotRegion(bed, stack = TRUE,

    panel.fun = function(region, value, ...) {

    circos.genomicRect(region, value, col = f(value[[1]]), border = NA, ...)

    })

    bed1 = generateRandomBed(nr = 100)

    bed2 = generateRandomBed(nr = 100)

    bed_list = list(bed1, bed2)

    circos.genomicTrackPlotRegion(bed_list, stack = TRUE,

    panel.fun = function(region, value, ...) {

    i = getI(...)

    circos.genomicRect(region, value, ytop = i + 0.4, ybottom = i - 0.4,

    col = f(value[[1]]), ...)

    })

    circos.genomicTrackPlotRegion(bed_list, ylim = c(0, 3),

    panel.fun = function(region, value, ...) {

    i = getI(...)

    circos.genomicRect(region, value, ytop = i + 0.4, ybottom = i - 0.4,

    col = f(value[[1]]), ...)

    })

    bed = generateRandomBed(nr = 200)

    circos.genomicTrackPlotRegion(bed,

    panel.fun = function(region, value, ...) {

    circos.genomicRect(region, value, ytop.column = 1, ybottom = 0,

    col = ifelse(value[[1]] > 0, "red", "green"), ...)

    cell.xlim = get.cell.meta.data("cell.xlim")

    circos.lines(cell.xlim, c(0, 0), lty = 2, col = "#00000040")

    })

    circos.clear()

    点到点,点到区间,区间到区间的连线:

    #构造数据

    bed1 = generateRandomBed(nr = 100)

    #抽提部分数据

    bed1 = bed1[sample(nrow(bed1), 20), ]

    bed2 = generateRandomBed(nr = 100)

    bed2 = bed2[sample(nrow(bed2), 20), ]

    #绘制轨道

    circos.initializeWithIdeogram(plotType = c("axis", "labels"))

    #区间到区间的连线

    circos.genomicLink(bed1, bed2)

    circos.clear()

    #我们也是可以着色的

    circos.initializeWithIdeogram(plotType = c("axis", "labels"))

    circos.genomicLink(bed1, bed2, col = rand_color(nrow(bed1), transparency = 0.5), border = NA)

    我们在基因组上也是可以高亮染色体信息的:

    circos.par("track.height" = 0.1)

    circos.initializeWithIdeogram(plotType = c("axis", "labels"))

    #绘制5条轨道

    for(i in 1:5) {

    bed = generateRandomBed(nr = 100)

    circos.genomicTrackPlotRegion(bed, panel.fun = function(region, value, ...) {

    circos.genomicPoints(region, value, pch = 16, cex = 0.5, ...)

    })

    }

    #高亮染色体

    highlight.chromosome(c("chrX", "chrY", "chr1"))

    highlight.chromosome("chr3", col = "#00FF0040", padding = c(0.05, 0.05, 0.15, 0.05))

    highlight.chromosome("chr5", col = NA, border = "red", lwd = 2, padding = c(0.05, 0.05, 0.15, 0.05))

    highlight.chromosome("chr7", col = "#0000FF40", track.index = c(2, 4, 5))

    highlight.chromosome(c("chr9", "chr10", "chr11"), col = NA, border = "green",lwd = 2, track.index = c(2, 4, 5))

    highlight.chromosome(paste0("chr", c(1:22, "X", "Y")), col = "#FFFF0040", track.index = 6)

    circos.clear()

    更多circlize信息,请看帮助文档……

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