## circos plot ### 应用场景 展示各组数据之间所占比例 >创建一个实例数据结构如下  ```R # 读取数据 load('./test_cir.Rdata') #rt_cir load('./color_list.Rdata') #color_list # 定义各个组的颜色 state_col <- color_list[3:25] names(state_col) <- c(colnames(rt_cir), row.names(rt_cir)) state_col2 <- state_col[4:23] colmat <- rep(state_col2, 3) dim(colmat) <- dim(rt_cir) ``` >作图 ```R # 简单的展示各个组别的数量大小和比例 circos.par(start.degree = 90, clock.wise = FALSE) cdm_res = chordDiagram(rt_cir, col = colmat, grid.col = state_col, directional = FALSE, annotationTrack = "grid", preAllocateTracks = list(track.height = 0.5)) ```  ```R # 为各个组别加上刻度标签 circos.par(start.degree = 90, clock.wise = FALSE) cdm_res = chordDiagram(rt_cir, col = colmat, grid.col = state_col, directional = FALSE, annotationTrack = "grid", preAllocateTracks = list(track.height = 0.5)) # 为各个组别刻度标签 circos.track(track.index = 2, panel.fun = function(x, y) { sector.index = get.cell.meta.data("sector.index") xlim = get.cell.meta.data("xlim") ylim = get.cell.meta.data("ylim") xlim = CELL_META$xlim breaks = seq(0, xlim[2], by = 5e4) circos.axis(major.at = breaks, labels = paste0(breaks/2000, "KB"), labels.cex = 0.5, minor.ticks = 1, labels.facing = "reverse.clockwise") }, bg.border = NA) ```  ```R # 加上一个比例刻度和组名 circos.par(start.degree = 90, clock.wise = FALSE) cdm_res = chordDiagram(rt_cir, col = colmat, grid.col = state_col, directional = FALSE, annotationTrack = "grid", preAllocateTracks = list(track.height = 0.5)) ### 为各个组别刻度标签 for(si in get.all.sector.index()) { circos.axis(h = "top", labels.cex = 0.3, sector.index = si, track.index = 2) } # the second axis as well as the sector labels are added in this track circos.track(track.index = 1, panel.fun = function(x, y) { xlim = get.cell.meta.data("xlim") ylim = get.cell.meta.data("ylim") sector.name = get.cell.meta.data("sector.index") xplot = get.cell.meta.data("xplot") circos.lines(xlim, c(mean(ylim), mean(ylim)), lty = 3) # dotted line by = ifelse(abs(xplot[2] - xplot[1]) > 30, 0.2, 0.5) for(p in seq(by, 1, by = by)) { circos.text(p*(xlim[2] - xlim[1]) + xlim[1], mean(ylim) + 0.1, paste0(p*100, "%"), cex = 0.3, adj = c(0.5, 0), niceFacing = TRUE) } circos.text(mean(xlim), 1, sector.name, niceFacing = TRUE, adj = c(0.5, 0)) }, bg.border = NA) circos.clear() ```  ```R # 为使图片看起来更加饱满，外围再重复叠加组别比列图 circos.par(start.degree = 90, clock.wise = FALSE) cdm_res = chordDiagram(rt_cir, col = colmat, grid.col = state_col, directional = FALSE, annotationTrack = "grid", preAllocateTracks = list(track.height = 0.5)) for(i in seq_len(nrow(cdm_res))) { if(cdm_res$value[i] > 0) { circos.rect(cdm_res[i, "x1"], -uy(3.5, "mm"), cdm_res[i, "x1"] - abs(cdm_res[i, "value"]), -uy(2.5, "mm"), col = state_col[cdm_res$cn[i]], border = state_col[cdm_res$cn[i]], sector.index = cdm_res$rn[i], track.index = 2) circos.rect(cdm_res[i, "x2"], -uy(3.5, "mm"), cdm_res[i, "x2"] - abs(cdm_res[i, "value"]), -uy(2.5, "mm"), col = state_col[cdm_res$rn[i]], border = state_col[cdm_res$rn[i]], sector.index = cdm_res$cn[i], track.index = 2) circos.rect(cdm_res[i, "x1"], -uy(-0.75, "mm"), cdm_res[i, "x1"] - abs(cdm_res[i, "value"]), -uy(-0.85, "mm"), col = state_col[cdm_res$cn[i]], border = state_col[cdm_res$cn[i]], sector.index = cdm_res$rn[i], track.index = 1) circos.rect(cdm_res[i, "x2"], -uy(-0.75, "mm"), cdm_res[i, "x2"] - abs(cdm_res[i, "value"]), -uy(-0.85, "mm"), col = state_col[cdm_res$rn[i]], border = state_col[cdm_res$rn[i]], sector.index = cdm_res$cn[i], track.index = 1) circos.rect(cdm_res[i, "x1"], -uy(-0.95, "mm"), cdm_res[i, "x1"] - abs(cdm_res[i, "value"]), -uy(-1.15, "mm"), col = state_col[cdm_res$rn[i]], border = state_col[cdm_res$rn[i]], sector.index = cdm_res$rn[i], track.index = 1) circos.rect(cdm_res[i, "x2"], -uy(-0.95, "mm"), cdm_res[i, "x2"] - abs(cdm_res[i, "value"]), -uy(-1.15, "mm"), col = state_col[cdm_res$cn[i]], border = state_col[cdm_res$cn[i]], sector.index = cdm_res$cn[i], track.index = 1) } } circos.track(track.index = 2, panel.fun = function(x, y) { sector.index = get.cell.meta.data("sector.index") xlim = get.cell.meta.data("xlim") ylim = get.cell.meta.data("ylim") xlim = CELL_META$xlim breaks = seq(0, xlim[2], by = 5e4) circos.axis(major.at = breaks, labels = paste0(breaks/2000, "KB"), labels.cex = 0.5, minor.ticks = 1, labels.facing = "reverse.clockwise") }, bg.border = NA) circos.track(track.index = 1, panel.fun = function(x, y) { sector.index = get.cell.meta.data("sector.index") xlim = get.cell.meta.data("xlim") ylim = get.cell.meta.data("ylim") circos.text(mean(xlim), 0.82, sector.index, cex = 0.7, facing = "reverse.clockwise", niceFacing = TRUE) xlim = CELL_META$xlim sector.name = get.cell.meta.data("sector.index") xplot = get.cell.meta.data("xplot") circos.lines(xlim, c(mean(ylim)/2.04, mean(ylim)/2.04), lty = 3) # dotted line by = ifelse(abs(xplot[2] - xplot[1]) > 30, 0.2, 0.5) for(p in seq(by, 1, by = by)) { circos.text(p*(xlim[2] - xlim[1]) + xlim[1], mean(ylim)/2.5, paste0(p*100, "%"), cex = 0.4, adj = c(0.5, 0), niceFacing = TRUE, facing = "reverse.clockwise") } }, bg.border = NA) circos.clear() ```