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1 ## fonction ###########################################################################
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2 plot_MLMM.Ago<-function(x) {
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3 output1 <-x$out[order(x$out$Pos),]
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4 output_ok<-output1[order(output1$Chr),]
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5
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6 maxpos<-c(0,cumsum(as.numeric(aggregate(output_ok$Pos,list(output_ok$Chr),max)$x+max(cumsum(as.numeric(aggregate(output_ok$Pos,list(output_ok$Chr),max)$x)))/200)))
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7 plot_col<-rep(c('gray10','gray60'),ceiling(max(unique(output_ok$Chr))/2))
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8 # plot_col<-c('blue','darkgreen','red','cyan','purple')
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9 size<-aggregate(output_ok$Pos,list(output_ok$Chr),length)$x
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10 a<-rep(maxpos[1],size[1])
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11 b<-rep(plot_col[1],size[1])
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12 for (i in 2:max(unique(output_ok$Chr))){
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13 a<-c(a,rep(maxpos[i],size[i]))
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14 b<-c(b,rep(plot_col[i],size[i]))}
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15
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16 output_ok$xpos<-output_ok$Pos+a
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17 output_ok$col<-b
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18 output_ok$col[output_ok$mk=='qtl']<-'cyan'
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19 output_ok$col[output_ok$SNP %in% x$cof]<-'red'
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20
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21 d<-(aggregate(output_ok$xpos,list(output_ok$Chr),min)$x+aggregate(output_ok$xpos,list(output_ok$Chr),max)$x)/2
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22
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23 plot(output_ok$xpos,-log10(output_ok$pval),col=output_ok$col,pch=20,ylab='-log10(pval)',xaxt='n',xlab='chromosome')
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24 axis(1,tick=FALSE,at=d,labels=c(1:max(unique(output_ok$Chr))))
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25 xline(output_ok$xpos[output_ok$mk=='qtl'], col='cyan', lwd=0.1)
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26 abline(h=x$bonf_thresh,lty=3,col='black')
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27
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28
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29 if (length(output_ok$pval[-log10(output_ok$pval) > x$bonf_thresh]) > 0) {
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30 text(output_ok$xpos[-log10(output_ok$pval) > x$bonf_thresh], -log10(output_ok$pval[-log10(output_ok$pval) > x$bonf_thresh]), output_ok$SNP[-log10(output_ok$pval) > x$bonf_thresh], pos=3, cex=0.7)
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31 legend("topright", lty=3, paste("bonf thresh :", x$bonf_thresh ,sep=" "))
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32 } else {
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33 legend("topright", lty=3, paste("bonf thresh :", x$bonf_thresh ,sep=" "))
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34 }
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35
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36 }
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