R语言可视化遗传连锁反应图谱

一粒沙

发布于 2021-07-28 15:43:35

1.9K0

发布于 2021-07-28 15:43:35

今天给大家介绍一个连锁图谱和数量性状位点（quantitative trait loci，QTL）图谱数据的可视化展示的包LinkageMapView。首先看下包的安装：

install.packages('LinkageMapView')

我们直接通过实例来给大家演示下这个包的使用：

library(LinkageMapView)
data(carrot)
head(carrot)

##简单的展示结果
lmv.linkage.plot(mapthis= carrot,outfile = 'g.pdf')

###为不同的标签增加颜色
flist <-list()
locus <-c("BSSR-094", "K0149", "K0627","K2161", "ESSR-087", "ESSR-057")
font  <- c(2)  #bold
flist[[1]]<- list(locus = locus, font = font)
locus <-c("F3H", "FLS1")
font  <- c(4)  #bold italic
flist[[2]]<- list(locus = locus, font = font)
locus <-c("P3", "P1", "Raa1")
font  <- c(3)  #italic
col <-c("red")
flist[[3]]<- list(locus = locus, font = font, col = col)
outfile = "carrot.pdf"
lmv.linkage.plot(
  carrot,
  outfile = outfile,
  ruler = TRUE,
  lgtitle = c("2170","70349", "10117"),
  maxnbrcolsfordups = 2,
  markerformatlist = flist,
  lg.col = "lightblue1",
  pdf.height = 16,
  pdf.width = 10
)

###添加连锁反应的区域
qtldf <-data.frame(
  chr = character(),
  qtl = character(),
  so = numeric(),
  si = numeric(),
  ei = numeric(),
  eo = numeric(),
  col = character(),
  stringsAsFactors = FALSE
)
qtldf <-rbind(qtldf,
               data.frame(
                 chr = "70349LG3",
                 qtl = "RTPE-Q1",
                 so = 36.6,
                 si = 37,
                 ei = 37,
                 eo = 38,
                 col="red"
               ))

outfile =file.path(tempdir(), "carrot.pdf")
lmv.linkage.plot(
  carrot,
  outfile = outfile,
  ruler = TRUE,
  lgtitle = c("2170","70349", "10117"),
  maxnbrcolsfordups = 2,
  markerformatlist = flist,
  lg.col = "lightblue1",
  pdf.height = 16,
  pdf.width = 10,
  revthese = c("70349LG3"),
  qtldf=qtldf
)

###qtl包数据的直接导入

library(qtl)
data(hyper)
class(hyper)
summary(hyper)

outfile = "hyper.pdf"
lmv.linkage.plot(hyper,outfile,mapthese=c(1,4,6,15))##mapthese指的染色体的名称

##为可视化结果添加标题
outfile ="hyper_titles.pdf"
lmv.linkage.plot(hyper,outfile,mapthese=c(1,4,6,15),col.lgtitle= "blue",cex.lgtitle=2,
col.main = "red",main="Overall Title for the OutputMap")

###标记同一位点出现多个标签的情况。
outfile = "hyper_dupnbr.pdf"
lmv.linkage.plot(hyper,outfile,mapthese=c(1,4,6,15),dupnbr= TRUE)

###只输出想要展示的位置的标签，需要用到shounonly参数
outfile ="hyper_showonly.pdf"
lmv.linkage.plot(hyper,outfile,mapthese=c(1,4,6,15),lcol="green",lcex=2,lfont=2,
    rcol="red",rcex=2,rfont=3,
   showonly=c("D1Mit123","D4Mit80","D6Mit135","D15Mit156"))

###绘制位点分布的密度图
## do a densitymap with default colors and customize the axis
data(oat)

## draw tickmarksat each cM from 0 to largest position of linkage groups to be drawn
maxpos <-floor(max(oat$Position[oat$Group == "Mrg01" | oat$Group =="Mrg02"]))
at.axis <-seq(0, maxpos)
 
## put labelson ruler at every 10 cM
axlab <-vector()
      for (lab in 0:maxpos) {
        if (!lab %% 10) {
          axlab <- c(axlab, lab)
        }
        else {
          axlab <- c(axlab, NA)
        }
      }
 
outfile = "oat_denmap.pdf"
lmv.linkage.plot(oat,outfile,mapthese=c("Mrg01","Mrg02"),denmap=TRUE,cex.axis = 1, at.axis = at.axis, labels.axis = axlab)