Transcript Ler/Shah QTL mapping - University of Chicago

Ler/Shah QTL mapping
Quantitative Trait Locus Analysis of GrowthRelated Traits in a New Arabidopsis
Recombinant Inbred Population1
Mohamed E. El-Lithy, Emile J.M. Clerkx, Gerda
J. Ruys, Maarten Koornneef and Dick
Vreugdenhil* Plant Physiol. 2004 May; 135(1):
432–443.
doi: 10.1104/pp.103.036814.
R statistical programming language
• http://cran.r-project.org download from a
local mirror. Any platform 2.3.1
• In R,
• > install.packages(c(“bqtl”,”qtl”))
• update.packages()
– Even for fresh install, perform weekly
• You may like WinEdt
– For text editing….
– > install.packages(“RWinEdt”)
Read in data
• Need, genotype data in R/QTL format
– Little excel formating work
• Example from Werner et al
– http://naturalvariation.org/werner
– Get
• Genotype/Phenotype data for Lz-0 x Ler F2 (A = Lz, B = Ler,
H = het)
• and script for QTL mapping output
• Line names and numbers from
– Arabidopsis.org
• search seed stock CS24481
Example Ler.Shah.csv
Missing data is NA, marker names must only have “.” not “-”, or “/”
Row1 header, row2 blank for traits chr for markers, row3 cM or blank
Genetic Map
Download setup file
http://naturalvariation.org/qtl/lershah.csv
We will add our trait data…
Read in code
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> setwd("../Ler.Shah") # set working directory
> #install.packages("qtl")
> library(qtl) # load qtl packag
> lersha <- read.cross(“csv”,file = "lershah.csv")
--Read the following data:
114 individuals
66 markers
1 phenotypes
--Estimating genetic map in: read.cross.csv(dir, file, na.strings, genotypes,
estimate.map,
> summary(lersha)
F2 intercross
No. individuals: 114
No. phenotypes: 1
Percent phenotyped: 100
No. chromosomes: 5
Total markers: 66
No. markers:
15 13 10 15 13
Percent genotyped: 98.8
Genotypes (%):
AA:54 AB:0 BB:46 not BB:0 not AA:0
> plot(lersha)
> source(“adjustri.R”)
> plot.map(adjustri(lersha, expand = F, type = "self"))
> image(pull.geno(lersha),col = topo.colors(2), xlab = “RILs”, ylab = “markers”)
Frequency distribution of nonnormalized data of some traits in the Ler x Sha RIL population
El-Lithy, M. E., et al. Plant Physiol. 2004;135:444-458
Copyright ©2004 American Society of Plant Biologists
95% by perms
> im <- adjustri(scanone(lersha,pheno.col = 1), expand = F, type = "self")
Warning message:
First running calc.genoprob. in: scanone(lersha, pheno.col = 1)
> plot(im,main = "names QTL Interval Map",ylim = c(0,10))
> abline(h = 3) # standard threshold..
sc2 <- scantwo(lersha,pheno.col = 1)
plot(sc2,main = "names QTL 2D Map")
bQTL
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map.list <- pull.map(adjustri(lersha, expand = F, type = "self"))
tmp.frm <- list()
for ( i in 1:length(map.list))
tmp.frm[[i]] <- data.frame(chr.num = i,
Marker = 1:length(map.list[[i]]),
marker.names = names(map.list[[i]]),
cM = as.numeric(map.list[[i]]) )
map.dx <- do.call("rbind", tmp.frm )
lersha.map.2 <- make.map.frame(map.dx,reso=2)
lersha.ana.2 <make.analysis.obj(lersha$pheno,lersha.map.2,pull.geno(lersha),
marker.levels=ri.levels(1,3,"NA"),
method="RI.self")
save(lersha.ana.2, file = "lersha.ana.2.RData", compress = T)
plot(lersha.ana.2)
Plot bQTL map
bQTL Interval Map
imap <- bqtl(CSstockNum ~ locus(all),lersha.ana.2)
# LOD conversion
lodL <- (loglik(imap)-min(loglik(imap)))*2/4.6
par(mfrow=c(2,3))
plot(lersha.ana.2,lodL)
bQTL Bayesian multigene
## linear bayes plots 10 gene model
lersha.LB.10LD <- linear.bayes(CSstockNum ~ locus(all), lersha.ana.2, rparm = 1,
specs = list(gene.number= 1:10,burn.in=1,n.cycles=c(0,0,200,rep(100,7))) )
## posterior odds plots
plot(lersha.ana.2, lersha.LB.10LD$loc.posterior, ylab = "Posterior Odds Ratio")
matplot(lersha.LB.10LD$specs$gene.number, lersha.LB.10LD$odds/
max(lersha.LB.10LD$odds),
xlab = "gene number", ylab = "relative fit", main = "multigene fit",type = "l")
## additive coefs
plot( ndc .ana.2, lersha.LB.10LD$coefficients, ylab = "additive effect")
plot(1,1,type="n",main = "additive coefs")
Posterior Odds ratio
Additive effects