通过画下方这张图，了解到plot/points/axis/legend的用法。
转载请注明出处~
代码
直接复制粘贴到R软件或者RStudio中，就可以把图画出来了，大多出代码有相应的解释~
rm(list=ls()) #清除环境#导入数据
Sample1 <- c(0:97) #对应非肿瘤组织的98个样本
Sample2 <- c(98:198) #对应肿瘤组织的101个样本
Non <- c(5789,6457,6922,7186,7370,7461,7552,7705,7760,7857,7901,7959,8011,8051,8092,8115,8148,8198,8228,8258,8277,8308,8333,8383,8399,8441,8459,8465,8490,8499,8507,8523,8536,8550,8556,8570,8578,8588,8594,8600,8607,8624,8634,8639,8650,8659,8668,8673,8677,8687,8692,8697,8707,8715,8721,8726,8738,8745,8753,8761,8764,8773,8779,8783,8786,8795,8798,8809,8811,8819,8821,8824,8826,8831,8833,8836,8837,8839,8841,8844,8852,8854,8856,8861,8863,8867,8870,8875,8877,8878,8881,8884,8888,8890,8894,8895,8898,8903)
Tumour <- c(8941,9009,9037,9045,9086,9137,9143,9147,9153,9159,9160,9168,9171,9181,9184,9191,9196,9198,9200,9204,9208,9214,9214,9216,9216,9218,9218,9222,9224,9224,9226,9228,9228,9229,9229,9229,9230,9232,9232,9235,9237,9237,9237,9238,9241,9245,9245,9245,9245,9245,9245,9246,9246,9247,9247,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9249,9249,9249,9249,9250,9251,9251,9251,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252)
all <- c(5789,6457,6922,7186,7370,7461,7552,7705,7760,7857,7901,7959,8011,8051,8092,8115,8148,8198,8228,8258,8277,8308,8333,8383,8399,8441,8459,8465,8490,8499,8507,8523,8536,8550,8556,8570,8578,8588,8594,8600,8607,8624,8634,8639,8650,8659,8668,8673,8677,8687,8692,8697,8707,8715,8721,8726,8738,8745,8753,8761,8764,8773,8779,8783,8786,8795,8798,8809,8811,8819,8821,8824,8826,8831,8833,8836,8837,8839,8841,8844,8852,8854,8856,8861,8863,8867,8870,8875,8877,8878,8881,8884,8888,8890,8894,8895,8898,8903,8941,9009,9037,9045,9086,9137,9143,9147,9153,9159,9160,9168,9171,9181,9184,9191,9196,9198,9200,9204,9208,9214,9214,9216,9216,9218,9218,9222,9224,9224,9226,9228,9228,9229,9229,9229,9230,9232,9232,9235,9237,9237,9237,9238,9241,9245,9245,9245,9245,9245,9245,9246,9246,9247,9247,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9248,9249,9249,9249,9249,9250,9251,9251,9251,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252,9252)s <- (0:198) #对应总的199个样本
plot(s,all,type = "l", #type选l，只画线条不画散点xlab = "Sample number",ylab = "Number of protein identifications",col="#eec693",lwd=4, #lwd线条宽度axes=F, #取消全部坐标轴及坐标框ylim=c(5000,10000), #设置y轴显示范围，不然默认不显示5000和10000，因为数据少cex.lab=1.3) #坐标轴标题的大小
points(Sample1,Non,col="#4d8ac9",pch=17) #画非肿瘤组织样本的散点
points(Sample2,Tumour,col="#f06a6b",pch=17) #画肿瘤组织样本的散点
legend(list(x=20,y=6100), #设置legend显示的位置bty="n", #不显示legend框title = NA, #没有标题c("Non-tumour","Tumour"),pch=c(17,17),col=c("#4d8ac9","#f06a6b"),horiz = T, #两个分组并排展示pt.cex = 2, #points的大小 cex = 1, #文字的大小text.font=2, #坐标标签“1”为正常，“2”为加粗，“3”为斜体text.col = "black", #文字的颜色text.width = strwidth("100000000000000")) #两个分组之间的间距，“0”越多间隔越大
axis(2,at=c(5000,6000,7000,8000,9000,10000), #2表示设置左坐标轴（y轴）label=c("5,000","6,000","7,000","8,000","9,000","10,000"),lwd=3,lwd.ticks = 3,font.axis=2, #坐标标签“1”为正常，“2”为加粗，“3”为斜体cex.axis=1) #坐标标签大小,默认为1
axis(1,seq(0,200,50),seq(0,200,50),lwd = 3,lwd.ticks = 3, #1表示设置下方坐标轴（x轴）font.axis=2)
