### R code from vignette source 'v-masbc.Rnw' ################################################### ### code chunk number 1: low_baseline_01 (eval = FALSE) ################################################### ## library(SelectionTools) ## options(width=72, digits=5) ## st.set.num.threads(1) ## ## st.output.dir <- file.path(tempdir(), "SelectionTools-masbc") ## st.data.dir <- st.output.dir ## dir.create(st.output.dir, recursive=TRUE, showWarnings=FALSE) ## ## NREP <- 10000 ## ## rng.init(seed=1001) ## reset.all() ################################################### ### code chunk number 2: low_baseline_02 (eval = FALSE) ################################################### ## data("lib00.map1") ## data("lib00.map1a") ## write.table(lib00.map1, file=file.path(st.output.dir,"mab-1.map"), ## quote=FALSE, row.names=FALSE, col.names=FALSE) ## write.table(lib00.map1a, file=file.path(st.output.dir,"mab-1a.map"), ## quote=FALSE, row.names=FALSE, col.names=FALSE) ## ## set.genome.par( ## no.chrom=10, ## no.hom=2, ## chrom.len=c(2.68,1.81,2.08,1.40,1.53, ## 1.56,0.93,1.44,1.55,1.14) ## ) ## load.linkage.map(file.path(st.output.dir,"mab-1.map")) ################################################### ### code chunk number 3: low_baseline_03 (eval = FALSE) ################################################### ## init.population("P1",homozygote(1)) ## init.population("P2",homozygote(8)) ## cross("F1","P1","P2",NREP) ## ## gen <- c("P1","F1","BC1","BC2","BC3","BC4","BC5","BC6") ## for (i in 1:7) ## cross(gen[i+1],gen[i],"P2",NREP) ## ## rpg <- genome.contribution("BC1 BC2 BC3 BC4 BC5 BC6",8) ## ## define.effects("markers80","0, mc 8 uniform 0.00625") ## estimated80 <- get.score("BC2","markers80") ## true80 <- evaluate.genome("BC2",8)$ratio ################################################### ### code chunk number 4: low_baseline_04 (eval = FALSE) ################################################### ## load.linkage.map(file.path(st.output.dir,"mab-1a.map")) ## define.effects("markers40","0, mc 8 uniform 0.0125") ## estimated40 <- get.score("BC2","markers40") ## true40 <- evaluate.genome("BC2",8)$ratio ## ## out <- list( ## recurrent.parent.genome=round(rpg,4), ## marker.estimate.correlation=c( ## markers80=cor(estimated80,true80), ## markers40=cor(estimated40,true40) ## ) ## ) ## print(out) ################################################### ### code chunk number 5: low_foreground_01 (eval = FALSE) ################################################### ## library(SelectionTools) ## options(width=72, digits=5) ## st.set.num.threads(1) ## ## st.output.dir <- file.path(tempdir(), "SelectionTools-masbc") ## st.data.dir <- st.output.dir ## dir.create(st.output.dir, recursive=TRUE, showWarnings=FALSE) ## ## NREP <- 10000 ## ## rng.init(seed=1002) ## reset.all() ################################################### ### code chunk number 6: low_foreground_02 (eval = FALSE) ################################################### ## data("lib00.map1") ## write.table(lib00.map1, file=file.path(st.output.dir,"mab-1.map"), ## quote=FALSE, row.names=FALSE, col.names=FALSE) ## ## set.genome.par( ## no.chrom=10, ## no.hom=2, ## chrom.len=c(2.68,1.81,2.08,1.40,1.53, ## 1.56,0.93,1.44,1.55,1.14) ## ) ## load.linkage.map(file.path(st.output.dir,"mab-1.map")) ## define.effects("target","0, target 1 uniform 1") ################################################### ### code chunk number 7: low_foreground_03 (eval = FALSE) ################################################### ## init.population("P1",homozygote(1)) ## init.population("P2",homozygote(8)) ## cross("F1","P1","P2",1) ## ## pop <- c("F1","BC1","BC2","BC3","BC4","BC5","BC6") ## se1 <- paste(pop,"s1",sep="") ## sel <- paste(pop,"se",sep="") ## store <- paste(pop,"st",sep="") ## sel[1] <- "F1" ################################################### ### code chunk number 8: low_foreground_04 (eval = FALSE) ################################################### ## for (j in 1:NREP) { ## for (i in 1:6) { ## cross(pop[i+1],sel[i],"P2",50) ## select.all.best(se1[i+1],pop[i+1],"target") ## sample.population(sel[i+1],se1[i+1],1) ## append.population(store[i+1],sel[i+1]) ## } ## } ################################################### ### code chunk number 9: low_foreground_05 (eval = FALSE) ################################################### ## out <- round( ## genome.contribution( ## "BC1st BC2st BC3st BC4st BC5st BC6st",8 ## ), ## 4 ## ) ## print(out) ################################################### ### code chunk number 10: low_two_stage_01 (eval = FALSE) ################################################### ## library(SelectionTools) ## options(width=72, digits=5) ## st.set.num.threads(1) ## ## st.output.dir <- file.path(tempdir(), "SelectionTools-masbc") ## st.data.dir <- st.output.dir ## dir.create(st.output.dir, recursive=TRUE, showWarnings=FALSE) ## ## NREP <- 10000 ## ## rng.init(seed=1003) ## reset.all() ################################################### ### code chunk number 11: low_two_stage_02 (eval = FALSE) ################################################### ## data("lib00.map1") ## write.table(lib00.map1, file=file.path(st.output.dir,"mab-1.map"), ## quote=FALSE, row.names=FALSE, col.names=FALSE) ## ## set.genome.par( ## no.chrom=10, ## no.hom=2, ## chrom.len=c(2.68,1.81,2.08,1.40,1.53, ## 1.56,0.93,1.44,1.55,1.14) ## ) ## load.linkage.map(file.path(st.output.dir,"mab-1.map")) ## define.effects("target","0, target 1 uniform 1") ## define.effects("markers","0, mc 8 uniform 0.00625") ################################################### ### code chunk number 12: low_two_stage_03 (eval = FALSE) ################################################### ## init.population("P1",homozygote(1)) ## init.population("P2",homozygote(8)) ## cross("F1","P1","P2",1) ## ## pop <- c("F1","BC1","BC2","BC3","BC4","BC5","BC6", ## "BC7","BC8","BC9","BC10") ## se1 <- paste(pop,"s1",sep="") ## se2 <- paste(pop,"s2",sep="") ## sel <- paste(pop,"se",sep="") ## store <- paste(pop,"st",sep="") ## sel[1] <- "F1" ## ## mdp <- matrix(NA_real_,nrow=10,ncol=NREP) ################################################### ### code chunk number 13: low_two_stage_04 (eval = FALSE) ################################################### ## for (j in 1:NREP) { ## reset.mdp() ## for (i in 1:10) { ## cross(pop[i+1],sel[i],"P2",100) ## select.all.best(se1[i+1],pop[i+1],"target") ## evaluate.mdp(se1[i+1],sel[i],"P2","markers") ## mdp[i,j] <- get.mdp() ## select.all.best(se2[i+1],se1[i+1],"markers") ## sample.population(sel[i+1],se2[i+1],1) ## append.population(store[i+1],sel[i+1]) ## } ## } ################################################### ### code chunk number 14: low_two_stage_05 (eval = FALSE) ################################################### ## out <- list( ## recurrent.parent.genome=round( ## genome.contribution( ## paste0("BC",1:10,"st",collapse=" "),8 ## ), ## 4 ## ), ## mean.marker.data.points=data.frame( ## generation=paste0("BC",1:10), ## MDP=round(rowMeans(mdp),1) ## ) ## ) ## print(out) ################################################### ### code chunk number 15: low_three_stage_01 (eval = FALSE) ################################################### ## library(SelectionTools) ## options(width=72, digits=5) ## st.set.num.threads(1) ## ## st.output.dir <- file.path(tempdir(), "SelectionTools-masbc") ## st.data.dir <- st.output.dir ## dir.create(st.output.dir, recursive=TRUE, showWarnings=FALSE) ## ## NREP <- 10000 ## ## rng.init(seed=1004) ## reset.all() ################################################### ### code chunk number 16: low_three_stage_02 (eval = FALSE) ################################################### ## data("lib00.map2") ## write.table(lib00.map2, file=file.path(st.output.dir,"mab-2.map"), ## quote=FALSE, row.names=FALSE, col.names=FALSE) ## ## set.genome.par( ## no.chrom=10, ## no.hom=2, ## chrom.len=c(2.68,1.81,2.08,1.40,1.53, ## 1.56,0.93,1.44,1.55,1.14) ## ) ## load.linkage.map(file.path(st.output.dir,"mab-2.map")) ## define.effects("target","0, target 1 uniform 1") ## define.effects("flanking","0, flanking 8 uniform 1") ## define.effects("markers","0, mc 8 uniform 1") ################################################### ### code chunk number 17: low_three_stage_03 (eval = FALSE) ################################################### ## init.population("P1",homozygote(1)) ## init.population("P2",homozygote(8)) ## cross("F1","P1","P2",1) ## ## pop <- c("F1","BC1","BC2","BC3","BC4","BC5","BC6") ## s1 <- paste(pop,"s1",sep="") ## s2 <- paste(pop,"s2",sep="") ## sel <- paste(pop,"se",sep="") ## store <- paste(pop,"st",sep="") ## sel[1] <- "F1" ## ## mdp <- matrix(NA_real_,nrow=6,ncol=NREP) ################################################### ### code chunk number 18: low_three_stage_04 (eval = FALSE) ################################################### ## for (j in 1:NREP) { ## reset.mdp() ## for (i in 1:6) { ## cross(pop[i+1],sel[i],"P2",100) ## select.all.best(s1[i+1],pop[i+1],"target") ## evaluate.mdp(s1[i+1],sel[i],"P2","flanking") ## select.all.best(s2[i+1],s1[i+1],"flanking") ## evaluate.mdp(s2[i+1],sel[i],"P2","markers") ## select.n.best(sel[i+1],s2[i+1],"markers",1) ## append.population(store[i+1],sel[i+1]) ## mdp[i,j] <- get.mdp() ## } ## } ################################################### ### code chunk number 19: low_three_stage_05 (eval = FALSE) ################################################### ## out <- list( ## recurrent.parent.genome=round( ## genome.contribution( ## "BC1st BC2st BC3st BC4st BC5st BC6st",8 ## ), ## 4 ## ), ## mean.marker.data.points=data.frame( ## generation=paste0("BC",1:6), ## MDP=round(rowMeans(mdp),1) ## ) ## ) ## print(out) ################################################### ### code chunk number 20: input_overview_01 (eval = FALSE) ################################################### ## # Input files have been prepared by the shared setup. ################################################### ### code chunk number 21: input_overview_02 (eval = FALSE) ################################################### ## map <- read.table( ## file.path(st.input.dir,"ex-mab1.map"), ## stringsAsFactors=FALSE ## ) ## names(map) <- c("chromosome","position.cM","locus") ################################################### ### code chunk number 22: input_overview_03 (eval = FALSE) ################################################### ## parent <- read.table( ## file.path(st.input.dir,"ex-mabp1_m.mda"), ## stringsAsFactors=FALSE, ## skip=1 ## ) ## parent.name <- scan( ## file.path(st.input.dir,"ex-mabp1_m.mda"), ## what="character", ## n=1, ## quiet=TRUE ## ) ################################################### ### code chunk number 23: input_overview_04 (eval = FALSE) ################################################### ## out <- list( ## map=head(map,6), ## parent.name=parent.name, ## parent.markers=head(parent,6) ## ) ## print(out) ################################################### ### code chunk number 24: high_core_01 (eval = FALSE) ################################################### ## rng.init(seed=2000) ################################################### ### code chunk number 25: high_core_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="core", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc"), ## population.size=c(1,100,100,100), ## sel.strategy=c("n","tfb","tfb","tfb"), ## result.file="core.RData" ## ) ################################################### ### code chunk number 26: high_core_03 (eval = FALSE) ################################################### ## loaded <- mab.load.data( ## simulation.name="core", ## simulation.run="x", ## result.file="core.RData" ## ) ################################################### ### code chunk number 27: high_core_04 (eval = FALSE) ################################################### ## tab <- mab.tabulate( ## simulation.names.runs=c("core","x"), ## ext.summary=TRUE, ## TargetAlleles=TRUE, ## RPG.gw.mean=TRUE, ## RPG.gw.Q10=TRUE, ## DonorSegments.gw=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files="core.RData" ## ) ################################################### ### code chunk number 28: high_core_05 (eval = FALSE) ################################################### ## out <- list( ## result.components=names(loaded), ## selected.summary=tab ## ) ## print(out) ################################################### ### code chunk number 29: ex01_01 (eval = FALSE) ################################################### ## rng.init(seed=2101) ################################################### ### code chunk number 30: ex01_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="fbm99-01", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc","bc","bc","bc","s","s"), ## population.size=c(1,100,100,100,100,100,100,100,100), ## sel.strategy=c("n","t","t","t","t","t","t","t","t"), ## result.file="fbm99-01.RData" ## ) ################################################### ### code chunk number 31: ex01_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c("fbm99-01","x"), ## TargetAlleles=TRUE, ## RPG.gw.mean=TRUE, ## LinkageDrag=TRUE, ## result.files="fbm99-01.RData" ## ) ## print(out) ################################################### ### code chunk number 32: ex02_01 (eval = FALSE) ################################################### ## rng.init(seed=2102) ################################################### ### code chunk number 33: ex02_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="fbm99-01", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc","bc","bc","bc","s","s"), ## population.size=c(1,100,100,100,100,100,100,100,100), ## sel.strategy=c("n","t","t","t","t","t","t","t","t"), ## result.file="fbm99-01.RData" ## ) ################################################### ### code chunk number 34: ex02_03 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="fbm99-02", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc","bc","bc"), ## population.size=c(1,100,100,100,100,100), ## sel.strategy=c("n","tb","tb","tb","tb","tb"), ## result.file="fbm99-02.RData" ## ) ################################################### ### code chunk number 35: ex02_04 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "fbm99-01","x", ## "fbm99-02","x" ## ), ## TargetAlleles=TRUE, ## RPG.gw.mean=TRUE, ## RPG.gw.Q10=TRUE, ## LinkageDrag=TRUE, ## result.files=c("fbm99-01.RData","fbm99-02.RData") ## ) ## print(out) ################################################### ### code chunk number 36: ex03_01 (eval = FALSE) ################################################### ## rng.init(seed=2103) ################################################### ### code chunk number 37: ex03_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="fbm99-03", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc"), ## population.size=c(1,33,100,166), ## sel.strategy=c("n","tfb","tfb","tfb"), ## result.file="fbm99-03.RData" ## ) ################################################### ### code chunk number 38: ex03_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c("fbm99-03","x"), ## RPG.gw.Q10=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files="fbm99-03.RData" ## ) ## print(out) ################################################### ### code chunk number 39: ex04_01 (eval = FALSE) ################################################### ## rng.init(seed=2104) ################################################### ### code chunk number 40: ex04_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="s01-060", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("f1","bc","bc","bc"), ## a.population.size=c(1,60,60,60), ## a.sel.strategy=c("n","tb","tb","tb"), ## b.simulation.name="s01-080", ## b.population.size=c(1,80,80,80), ## c.simulation.name="s01-100", ## c.population.size=c(1,100,100,100), ## d.simulation.name="s01-125", ## d.population.size=c(1,125,125,125), ## e.simulation.name="s01-150", ## e.population.size=c(1,150,150,150), ## f.simulation.name="s01-200", ## f.population.size=c(1,200,200,200), ## result.files=c( ## "s01-060.RData", ## "s01-080.RData", ## "s01-100.RData", ## "s01-125.RData", ## "s01-150.RData", ## "s01-200.RData" ## ) ## ) ################################################### ### code chunk number 41: ex04_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "s01-060","x", ## "s01-080","x", ## "s01-100","x", ## "s01-125","x", ## "s01-150","x", ## "s01-200","x" ## ), ## RPG.gw.Q10=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files=c( ## "s01-060.RData", ## "s01-080.RData", ## "s01-100.RData", ## "s01-125.RData", ## "s01-150.RData", ## "s01-200.RData" ## ) ## ) ## print(out) ################################################### ### code chunk number 42: ex05_01 (eval = FALSE) ################################################### ## rng.init(seed=2105) ################################################### ### code chunk number 43: ex05_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="fm01u-01", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab2.map", ## target.loci=c("target1","target2"), ## flanking.loci=c("umc90","umc27","umc111","bnl1407"), ## gen.type=c("f1","bc","bc","bc"), ## population.size=c(1,60,120,180), ## sel.strategy=c("n","tfb","tfb","tfb"), ## result.file="fm01u-01.RData" ## ) ################################################### ### code chunk number 44: ex05_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c("fm01u-01","x"), ## TargetAlleles=TRUE, ## RPG.gw.mean=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files="fm01u-01.RData" ## ) ## print(out) ################################################### ### code chunk number 45: ex06_01 (eval = FALSE) ################################################### ## rng.init(seed=2106) ################################################### ### code chunk number 46: ex06_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="ld-t", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("f1","bc","bc","bc"), ## a.population.size=c(1,100,100,100), ## a.sel.strategy=c("n","t","t","t"), ## a.no.selected=c(1,1,1,1), ## b.simulation.name="ld-tb", ## b.sel.strategy=c("n","tb","tb","tb"), ## c.simulation.name="ld-tfb", ## c.sel.strategy=c("n","tfb","tfb","tfb"), ## result.files=c("ld-t.RData","ld-tb.RData","ld-tfb.RData") ## ) ################################################### ### code chunk number 47: ex06_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "ld-t","x", ## "ld-tb","x", ## "ld-tfb","x" ## ), ## RPG.gw.Q10=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files=c("ld-t.RData","ld-tb.RData","ld-tfb.RData") ## ) ## print(out) ################################################### ### code chunk number 48: ex07_01 (eval = FALSE) ################################################### ## rng.init(seed=2107) ################################################### ### code chunk number 49: ex07_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="fm013g-01", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.linkage.map="ex-mab3.map", ## a.target.loci=c("target1","target2","target3"), ## a.flanking.loci=c( ## "umc90","umc27", ## "umc111","bnl1407", ## "umc37","bnl1518" ## ), ## a.gen.type=c("f1","bc","bc","bc"), ## a.population.size=c(1,100,100,100), ## a.sel.strategy=c("n","t","t","t"), ## b.simulation.name="fm013g-02", ## b.sel.strategy=c("n","tb","tb","tb"), ## c.simulation.name="fm013g-03", ## c.sel.strategy=c("n","tfb","tfb","tfb"), ## d.simulation.name="fm013g-04", ## d.population.size=c(1,200,100,100), ## d.sel.strategy=c("n","tfb","tb","tb"), ## result.files=c( ## "fm013g-01.RData", ## "fm013g-02.RData", ## "fm013g-03.RData", ## "fm013g-04.RData" ## ) ## ) ################################################### ### code chunk number 50: ex07_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "fm013g-01","x", ## "fm013g-02","x", ## "fm013g-03","x", ## "fm013g-04","x" ## ), ## RPG.gw.Q10=TRUE, ## TargetAlleles=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files=c( ## "fm013g-01.RData", ## "fm013g-02.RData", ## "fm013g-03.RData", ## "fm013g-04.RData" ## ) ## ) ## print(out) ################################################### ### code chunk number 51: ex08_01 (eval = FALSE) ################################################### ## rng.init(seed=2108) ################################################### ### code chunk number 52: ex08_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="marker-01", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.donor.parent="ex-mabp1_m.mda", ## a.recurrent.parent="ex-mabp2_m.mda", ## a.linkage.map="ex-mab4.map", ## a.target.loci="s7e2190xxx", ## a.flanking.loci=c("s7e5163xxx","s7e4815xxx"), ## a.gen.type=c("f1","bc","bc"), ## a.population.size=c(1,25,25), ## a.sel.strategy=c("n","t","t"), ## a.missing.allele="9", ## b.simulation.name="marker-02", ## b.population.size=c(1,50,50), ## b.sel.strategy=c("n","tb","tb"), ## result.files=c("marker-01.RData","marker-02.RData") ## ) ################################################### ### code chunk number 53: ex08_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "marker-01","x", ## "marker-02","x" ## ), ## RPG.gw.Q10=TRUE, ## DonorSegments.gw=TRUE, ## LinkageDrag=TRUE, ## result.files=c("marker-01.RData","marker-02.RData") ## ) ## print(out) ################################################### ### code chunk number 54: ex09_01 (eval = FALSE) ################################################### ## rng.init(seed=2109) ################################################### ### code chunk number 55: ex09_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="bc1i1tfb", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.donor.parent="ex-mabi1.mda", ## a.recurrent.parent="ex-mabp2.mda", ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("bc","bc"), ## a.population.size=c(100,100), ## a.sel.strategy=c("tfb","tfb"), ## b.simulation.name="bc1i2tfb", ## b.donor.parent="ex-mabi2.mda", ## c.simulation.name="bc1i3tfb", ## c.donor.parent="ex-mabi3.mda", ## d.simulation.name="bc1i4tfb", ## d.donor.parent="ex-mabi4.mda", ## e.simulation.name="bc1i5tfb", ## e.donor.parent="ex-mabi5.mda", ## f.simulation.name="bc1i6tfb", ## f.donor.parent="ex-mabi6.mda", ## result.files=paste0("bc1i",1:6,"tfb.RData") ## ) ################################################### ### code chunk number 56: ex09_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=as.vector(rbind( ## paste0("bc1i",1:6,"tfb"), ## rep("x",6) ## )), ## RPG.gw.Q10=TRUE, ## DonorSegments.gw=TRUE, ## LinkageDrag=TRUE, ## result.files=paste0("bc1i",1:6,"tfb.RData") ## ) ## print(out) ################################################### ### code chunk number 57: ex09a_01 (eval = FALSE) ################################################### ## rng.init(seed=2110) ################################################### ### code chunk number 58: ex09a_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="bc1i1", ## a.simulation.run="x", ## a.donor.parent="ex-mabi1.mda", ## a.recurrent.parent="ex-mabp2.mda", ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## b.simulation.name="bc1i2", ## b.donor.parent="ex-mabi2.mda", ## c.simulation.name="bc1i3", ## c.donor.parent="ex-mabi3.mda", ## d.simulation.name="bc1i4", ## d.donor.parent="ex-mabi4.mda", ## e.simulation.name="bc1i5", ## e.donor.parent="ex-mabi5.mda", ## f.simulation.name="bc1i6", ## f.donor.parent="ex-mabi6.mda", ## result.files=paste0("bc1i",1:6,".RData") ## ) ################################################### ### code chunk number 59: ex09a_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=as.vector(rbind( ## paste0("bc1i",1:6), ## rep("x",6) ## )), ## RPG.gw.Q10=TRUE, ## DonorSegments.gw=TRUE, ## LinkageDrag=TRUE, ## result.files=paste0("bc1i",1:6,".RData") ## ) ## print(out) ################################################### ### code chunk number 60: ex10_01 (eval = FALSE) ################################################### ## rng.init(seed=2111) ################################################### ### code chunk number 61: ex10_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="bc1i1tfs", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.donor.parent="ex-mabi1.mda", ## a.recurrent.parent="ex-mabp2.mda", ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("bc","bc"), ## a.population.size=c(100,100), ## a.sel.strategy=c("tfs","tfs"), ## a.no.selected=c(1,1), ## b.simulation.name="bc1i2tfs", ## b.donor.parent="ex-mabi2.mda", ## c.simulation.name="bc1i3tfs", ## c.donor.parent="ex-mabi3.mda", ## d.simulation.name="bc1i4tfs", ## d.donor.parent="ex-mabi4.mda", ## e.simulation.name="bc1i5tfs", ## e.donor.parent="ex-mabi5.mda", ## f.simulation.name="bc1i6tfs", ## f.donor.parent="ex-mabi6.mda", ## result.files=paste0("bc1i",1:6,"tfs.RData") ## ) ################################################### ### code chunk number 62: ex10_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=as.vector(rbind( ## paste0("bc1i",1:6,"tfs"), ## rep("x",6) ## )), ## RPG.gw.Q10=TRUE, ## DonorSegments.gw=TRUE, ## LinkageDrag=TRUE, ## result.files=paste0("bc1i",1:6,"tfs.RData") ## ) ## print(out) ################################################### ### code chunk number 63: ex11_01 (eval = FALSE) ################################################### ## rng.init(seed=2112) ################################################### ### code chunk number 64: ex11_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="regions-1", ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## gen.type=c("f1","bc","bc","bc"), ## population.size=c(1,500,500,500), ## sel.strategy=c("n","t","t","t"), ## no.selected=c(1,1,1,1), ## reg.chr=c(1,5,5), ## reg.begin=c(0,0,0), ## reg.end=c(0,0,60), ## result.file="regions-1.RData" ## ) ################################################### ### code chunk number 65: ex11_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c("regions-1","x"), ## ext.summary=TRUE, ## RPG.gw.mean=TRUE, ## RPG.reg.mean=TRUE, ## DonorSegments.gw=TRUE, ## DonorSegments.reg=TRUE, ## result.files="regions-1.RData" ## ) ## print(out) ################################################### ### code chunk number 66: ex12_01 (eval = FALSE) ################################################### ## recipient <- c( ## "bnl845","umc53","umc6","umc34","umc131", ## "umc98a","umc4","umc10","bnl844b","umc36" ## ) ################################################### ### code chunk number 67: ex12_02 (eval = FALSE) ################################################### ## run.recipient <- function(name,strategy,seed) { ## rng.init(seed=seed) ## mab.simulate( ## simulation.name=name, ## simulation.run="x", ## repetitions=NREP, ## linkage.map="ex-mab1.map", ## target.loci="target", ## flanking.loci=c("umc90","umc27"), ## recipient.loci=recipient, ## gen.type=c("f1","bc","bc","bc"), ## population.size=c(1,1000,1000,1000), ## sel.strategy=c("n",strategy,strategy,strategy), ## no.selected=c(1,1,1,1), ## reg.chr=c(1,2,5,5), ## reg.begin=c(0,0,0,0), ## reg.end=c(0,0,0,60), ## result.file=paste0(name,".RData") ## ) ## } ################################################### ### code chunk number 68: ex12_03 (eval = FALSE) ################################################### ## run.recipient("ss-t", "t", 21131) ## run.recipient("ss-tf", "tf", 21132) ## run.recipient("ss-tr", "tr", 21133) ## run.recipient("ss-tfb", "tfb", 21134) ## run.recipient("ss-trb", "trb", 21135) ## run.recipient("ss-trfb","trfb",21136) ## run.recipient("ss-tfrb","tfrb",21137) ################################################### ### code chunk number 69: ex12_04 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "ss-t","x", ## "ss-tf","x", ## "ss-tr","x", ## "ss-tfb","x", ## "ss-trb","x", ## "ss-trfb","x", ## "ss-tfrb","x" ## ), ## ext.summary=TRUE, ## RPG.gw.mean=TRUE, ## RPG.reg.mean=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files=c( ## "ss-t.RData","ss-tf.RData","ss-tr.RData", ## "ss-tfb.RData","ss-trb.RData", ## "ss-trfb.RData","ss-tfrb.RData" ## ) ## ) ## print(out) ################################################### ### code chunk number 70: ex13_01 (eval = FALSE) ################################################### ## rng.init(seed=2114) ################################################### ### code chunk number 71: ex13_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="success-1", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("f1","bc","bc","bc","bc","bc"), ## a.population.size=c(1,100,100,100,100,100), ## a.sel.strategy=c("n","tb","tb","tb","tb","tb"), ## a.no.selected=c(1,10,10,10,10,10), ## a.success.factor=1, ## b.simulation.name="success-2", ## b.no.selected=c(1,10,10,10,10,10), ## b.success.factor=0.5, ## c.simulation.name="success-3", ## c.no.selected=c(1,5,5,5,5,5), ## c.success.factor=1, ## result.files=c( ## "success-1.RData", ## "success-2.RData", ## "success-3.RData" ## ) ## ) ################################################### ### code chunk number 72: ex13_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "success-1","x", ## "success-2","x", ## "success-3","x" ## ), ## ext.summary=TRUE, ## RPG.gw.mean=TRUE, ## RPG.gw.Q10=TRUE, ## result.files=c( ## "success-1.RData", ## "success-2.RData", ## "success-3.RData" ## ) ## ) ## print(out) ################################################### ### code chunk number 73: ex14_01 (eval = FALSE) ################################################### ## rng.init(seed=2115) ################################################### ### code chunk number 74: ex14_02 (eval = FALSE) ################################################### ## mab.simulate( ## simulation.name="rec-01", ## simulation.run="x", ## donor.parent="ex-mabp1_m.mda", ## recurrent.parent="ex-mabp2_m.mda", ## linkage.map="ex-mab4.map", ## result.file="rec-01.RData", ## recode.infiles=TRUE, ## recode.file="recoded-parents.mda" ## ) ################################################### ### code chunk number 75: ex14_03 (eval = FALSE) ################################################### ## out <- list( ## result=names(mab.load.data( ## simulation.name="rec-01", ## simulation.run="x", ## result.file="rec-01.RData" ## )), ## recoded.file=head( ## readLines(file.path(st.output.dir,"recoded-parents.mda")), ## 12 ## ) ## ) ## print(out) ################################################### ### code chunk number 76: ex15_01 (eval = FALSE) ################################################### ## rng.init(seed=2116) ################################################### ### code chunk number 77: ex15_02 (eval = FALSE) ################################################### ## mab.compare( ## a.simulation.name="sel-50-0a-01", ## a.simulation.run="x", ## a.repetitions=NREP, ## a.linkage.map="ex-mab1.map", ## a.target.loci="target", ## a.flanking.loci=c("umc90","umc27"), ## a.gen.type=c("f1","bc","bc","bc"), ## a.population.size=c(1,50,50,50), ## a.sel.strategy=c("n","tfb","tfb","tfb"), ## b.simulation.name="sel-50-05-01", ## b.no.preselected=c(1,5,5,5), ## result.files=c("sel-50-0a-01.RData","sel-50-05-01.RData") ## ) ################################################### ### code chunk number 78: ex15_03 (eval = FALSE) ################################################### ## out <- mab.tabulate( ## simulation.names.runs=c( ## "sel-50-0a-01","x", ## "sel-50-05-01","x" ## ), ## ext.summary=TRUE, ## RPG.gw.Q10=TRUE, ## LinkageDrag=TRUE, ## MarkerAnalyses=TRUE, ## result.files=c("sel-50-0a-01.RData","sel-50-05-01.RData") ## ) ## print(out)