tests/testthat/test-convert2geno.R
In kbroman/simcross: Simulate Experimental Crosses
context("convert2geno")
test_that("convert2geno works for 2-allele case", {
# data as list with alleles in intervals
# (as produced by sim_from_pedigree)
dat <- list("1" = list(mat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L),
locations = c(1.63593688048422, 50.6488258950412,
54.441562271677, 72.7342922240496,
80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
82.6503853080794, 90.0170957203954,
91.0740879364312, 100))),
"2" = list(mat = list(alleles = c(1L, 2L, 1L, 2L, 1L),
locations = c(1.72073859721422, 2.41351707372814,
72.7342922240496, 80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
54.1366793680936, 75.1830249791965,
82.6503853080794, 90.0170957203954,
91.0740879364312, 100))),
"3" = list(mat = list(alleles = c(1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(1.72073859721422, 2.41351707372814,
50.6488258950412, 54.441562271677,
89.9764276109636, 97.2906407434493, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
97.3880127770826, 100))),
"4" = list(mat = list(alleles = c(2L, 1L, 2L, 1L),
locations = c(1.63593688048422, 72.7342922240496,
80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(20.5045772017911, 38.2374913664535,
48.7418097676709, 75.1830249791965,
82.6503853080794, 88.3461387362331,
97.3880127770826, 100))))
# marker map
map <- seq(0, 100, by=5)
names(map) <- paste0("marker", seq(along=map))
# expected genotype matrix (force integers)
expected <- rbind(c(3, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 1, 1, 1, 1),
c(2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 3, 1, 1, 1, 1),
c(2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 1),
c(3, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 2, 1))
storage.mode(expected) <- "integer"
dimnames(expected) <- list(as.character(1:4), paste0("marker", 1:21))
expect_equal(expected, convert2geno(dat, map))
# with founder genotypes
founder_geno <- rbind(rep(1, length(map)),
rep(2, length(map)))
expect_equal(expected, convert2geno(dat, map, founder_geno))
# switch founder alleles
founder_geno <- rbind(rep(2, length(map)),
rep(1, length(map)))
expected2 <- 4 - expected
expect_equal(expected2, convert2geno(dat, map, founder_geno))
# random founder alleles
founder_geno <- rbind(c(2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1,
2, 2, 2, 1, 1, 2),
c(2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2,
2, 2, 1, 2, 2, 2))
expected3 <- expected
for(i in 1:ncol(expected3)) {
if(founder_geno[1,i]==1 & founder_geno[2,i]==1)
expected3[,i] <- 1
else if(founder_geno[1,i]==2 & founder_geno[2,i]==2)
expected3[,i] <- 3
else if(founder_geno[1,i]==2 & founder_geno[2,i]==1)
expected3[,i] <- 4-expected[,i]
}
expect_equal(expected3, convert2geno(dat, map, founder_geno))
})
test_that("convert2geno works for 8-allele case", {
# data as list with alleles in intervals
# (as produced by sim_from_pedigree)
dat <- list("1" = list(mat = list(alleles=c(8L, 2L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 18.4184361249208,
55.8109006844461, 86.3054546294734,
88.7538079405203, 90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.0876344339922, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"2" = list(mat = list(alleles=c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.7756949001923, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
29.4709661742672, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"3" = list(mat = list(alleles=c(8L, 2L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 18.4184361249208,
55.8109006844461, 86.3054546294734,
88.7538079405203, 90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.7756949001923, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"4" = list(mat = list(alleles=c(8L, 2L, 8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 12.613788805902,
21.6286054579541, 27.2114308550954,
32.0876344339922, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
29.4709661742672, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))))
# marker map
map <- seq(0, 100, by=5)
names(map) <- paste0("marker", seq(along=map))
# Use get_geno to construct expected array
expected <- array(dim=c(length(dat), length(map), 2))
dimnames(expected) <- list(names(dat), names(map), c("mat", "pat"))
for(i in seq(along=map))
expected[,i,] <- get_geno(dat, map[i])
storage.mode(expected) <- "integer"
expect_equal(expected, convert2geno(dat, map))
# now test with use of founder genotypes
founder_geno <- rbind(c(2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1,
2, 1, 1, 1, 2, 2),
c(2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2,
1, 1, 2, 1, 1, 2),
c(2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2,
1, 2, 2, 2, 1, 1),
c(1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2,
2, 1, 1, 2, 1, 1),
c(2, 2, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2,
1, 2, 2, 2, 1, 2),
c(1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1,
1, 2, 2, 1, 1, 2),
c(2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1,
1, 2, 2, 2, 1, 1),
c(2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2,
2, 2, 2, 2, 1, 1))
storage.mode(founder_geno) <- "integer"
expected2 <- rbind(c(3, 3, 3, 2, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 1, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 2, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 1, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1))
storage.mode(expected2) <- "integer"
dimnames(expected2) <- list(as.character(1:4), paste0("marker", 1:21))
expect_equal(expected2, convert2geno(dat, map, founder_geno))
})
test_that("convert2geno and get_geno give same answer when shifted", {
# marker map starting at 5
map <- seq(20, 80, by=5)
names(map) <- paste0("marker", seq(along=map))
# simulate large ail pedigree
set.seed(37513076)
tab <- sim_ail_pedigree(6, 100)
dat <- sim_from_pedigree(tab, max(map))[tab[,"gen"]==6]
g <- convert2geno(dat, map)
g_shifted <- convert2geno(dat, map, shift_map=TRUE)
expect_equal(g[,map==30], g_shifted[,map==50])
qtl_g <- get_geno(dat, 30)
qtl_g <- (qtl_g[,1] + qtl_g[,2] - 1)
expect_equal(qtl_g, g[,map==30])
expect_equal(qtl_g, g_shifted[,map==50])
})
kbroman/simcross documentation built on Jan. 13, 2024, 10:31 p.m.
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context("convert2geno")
test_that("convert2geno works for 2-allele case", {
# data as list with alleles in intervals
# (as produced by sim_from_pedigree)
dat <- list("1" = list(mat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L),
locations = c(1.63593688048422, 50.6488258950412,
54.441562271677, 72.7342922240496,
80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
82.6503853080794, 90.0170957203954,
91.0740879364312, 100))),
"2" = list(mat = list(alleles = c(1L, 2L, 1L, 2L, 1L),
locations = c(1.72073859721422, 2.41351707372814,
72.7342922240496, 80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
54.1366793680936, 75.1830249791965,
82.6503853080794, 90.0170957203954,
91.0740879364312, 100))),
"3" = list(mat = list(alleles = c(1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(1.72073859721422, 2.41351707372814,
50.6488258950412, 54.441562271677,
89.9764276109636, 97.2906407434493, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L),
locations = c(8.94253242295235, 43.9252462703735,
97.3880127770826, 100))),
"4" = list(mat = list(alleles = c(2L, 1L, 2L, 1L),
locations = c(1.63593688048422, 72.7342922240496,
80.7659703074023, 100)),
pat = list(alleles = c(2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L),
locations = c(20.5045772017911, 38.2374913664535,
48.7418097676709, 75.1830249791965,
82.6503853080794, 88.3461387362331,
97.3880127770826, 100))))
# marker map
map <- seq(0, 100, by=5)
names(map) <- paste0("marker", seq(along=map))
# expected genotype matrix (force integers)
expected <- rbind(c(3, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 1, 1, 1, 1),
c(2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 2, 3, 1, 1, 1, 1),
c(2, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 1),
c(3, 2, 2, 2, 2, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 2, 3, 1, 2, 2, 1))
storage.mode(expected) <- "integer"
dimnames(expected) <- list(as.character(1:4), paste0("marker", 1:21))
expect_equal(expected, convert2geno(dat, map))
# with founder genotypes
founder_geno <- rbind(rep(1, length(map)),
rep(2, length(map)))
expect_equal(expected, convert2geno(dat, map, founder_geno))
# switch founder alleles
founder_geno <- rbind(rep(2, length(map)),
rep(1, length(map)))
expected2 <- 4 - expected
expect_equal(expected2, convert2geno(dat, map, founder_geno))
# random founder alleles
founder_geno <- rbind(c(2, 1, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2, 1, 2, 1,
2, 2, 2, 1, 1, 2),
c(2, 1, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 1, 2,
2, 2, 1, 2, 2, 2))
expected3 <- expected
for(i in 1:ncol(expected3)) {
if(founder_geno[1,i]==1 & founder_geno[2,i]==1)
expected3[,i] <- 1
else if(founder_geno[1,i]==2 & founder_geno[2,i]==2)
expected3[,i] <- 3
else if(founder_geno[1,i]==2 & founder_geno[2,i]==1)
expected3[,i] <- 4-expected[,i]
}
expect_equal(expected3, convert2geno(dat, map, founder_geno))
})
test_that("convert2geno works for 8-allele case", {
# data as list with alleles in intervals
# (as produced by sim_from_pedigree)
dat <- list("1" = list(mat = list(alleles=c(8L, 2L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 18.4184361249208,
55.8109006844461, 86.3054546294734,
88.7538079405203, 90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.0876344339922, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"2" = list(mat = list(alleles=c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.7756949001923, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
29.4709661742672, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"3" = list(mat = list(alleles=c(8L, 2L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 18.4184361249208,
55.8109006844461, 86.3054546294734,
88.7538079405203, 90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
32.7756949001923, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))),
"4" = list(mat = list(alleles=c(8L, 2L, 8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(8.20657967124134, 12.613788805902,
21.6286054579541, 27.2114308550954,
32.0876344339922, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100)),
pat = list(alleles = c(8L, 2L, 1L, 8L, 5L, 3L, 5L, 3L),
locations=c(21.6286054579541, 27.2114308550954,
29.4709661742672, 55.8109006844461,
86.3054546294734, 88.7538079405203,
90.0979985482991, 100))))
# marker map
map <- seq(0, 100, by=5)
names(map) <- paste0("marker", seq(along=map))
# Use get_geno to construct expected array
expected <- array(dim=c(length(dat), length(map), 2))
dimnames(expected) <- list(names(dat), names(map), c("mat", "pat"))
for(i in seq(along=map))
expected[,i,] <- get_geno(dat, map[i])
storage.mode(expected) <- "integer"
expect_equal(expected, convert2geno(dat, map))
# now test with use of founder genotypes
founder_geno <- rbind(c(2, 2, 2, 2, 2, 1, 2, 2, 2, 1, 1, 2, 1, 1, 1,
2, 1, 1, 1, 2, 2),
c(2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 2, 2,
1, 1, 2, 1, 1, 2),
c(2, 2, 1, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 2,
1, 2, 2, 2, 1, 1),
c(1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 2,
2, 1, 1, 2, 1, 1),
c(2, 2, 1, 1, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2,
1, 2, 2, 2, 1, 2),
c(1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 2, 2, 1, 1,
1, 2, 2, 1, 1, 2),
c(2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 1, 2, 2, 2, 1,
1, 2, 2, 2, 1, 1),
c(2, 2, 2, 1, 1, 2, 1, 1, 2, 2, 2, 2, 2, 1, 2,
2, 2, 2, 2, 1, 1))
storage.mode(founder_geno) <- "integer"
expected2 <- rbind(c(3, 3, 3, 2, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 1, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 2, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1),
c(3, 3, 3, 1, 1, 3, 2, 1, 3, 3, 3, 3, 3, 1, 3, 1,
3, 3, 3, 1, 1))
storage.mode(expected2) <- "integer"
dimnames(expected2) <- list(as.character(1:4), paste0("marker", 1:21))
expect_equal(expected2, convert2geno(dat, map, founder_geno))
})
test_that("convert2geno and get_geno give same answer when shifted", {
# marker map starting at 5
map <- seq(20, 80, by=5)
names(map) <- paste0("marker", seq(along=map))
# simulate large ail pedigree
set.seed(37513076)
tab <- sim_ail_pedigree(6, 100)
dat <- sim_from_pedigree(tab, max(map))[tab[,"gen"]==6]
g <- convert2geno(dat, map)
g_shifted <- convert2geno(dat, map, shift_map=TRUE)
expect_equal(g[,map==30], g_shifted[,map==50])
qtl_g <- get_geno(dat, 30)
qtl_g <- (qtl_g[,1] + qtl_g[,2] - 1)
expect_equal(qtl_g, g[,map==30])
expect_equal(qtl_g, g_shifted[,map==50])
})
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