tests/testthat/test-qtleffects.R

context("QTL effects")

test_that("estQTLeffects works for RIL by selfing", {

    data(grav)
    grav <- qtl::reduce2grid(qtl::calc.genoprob(grav[1:2,], step=5))

    pr <- qtl::pull.genoprob(grav, omit.first.prob=TRUE)

    pheno.col <- 1:5
    eff <- apply(pr, 2, function(a,b) lm(b ~ a)$coef[2,]/2, as.matrix(grav$pheno[,pheno.col]))
    eff <- lapply(as.data.frame(eff), as.matrix)

    expect_equivalent( estQTLeffects(grav, pheno.col=pheno.col, "effects"), eff )
    expect_equivalent( lapply(estQTLeffects(grav, pheno.col=pheno.col), function(a) matrix((a[,2]-a[,1])/2)), eff )

})

test_that("estQTLeffects works for X chromosome in F2", {

    library(qtl)
    data(fake.f2)
    fake.f2 <- qtl::calc.genoprob(fake.f2["X",])

    pr <- qtl::reviseXdata("f2", "standard", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                           cross.attr=attributes(fake.f2))

    pheno.col <- 1
    eff <- apply(pr, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))

    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col), eff )

    pr_alt <- qtl::reviseXdata("f2", "full", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                               cross.attr=attributes(fake.f2))
    eff <- apply(pr_alt, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))
    eff.a <- lapply(eff, function(a) matrix(a[seq(2,length(a), by=2)] - a[seq(1,length(a), by=2)], nrow=1))
    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col, "effects"), eff.a )

    # treat as all males
    origsex <- fake.f2$pheno$sex
    fake.f2$pheno$sex <- rep(1, nind(fake.f2))

    pr <- qtl::reviseXdata("f2", "standard", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                           cross.attr=attributes(fake.f2))

    pheno.col <- 1
    eff <- apply(pr, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))

    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col), eff )

    eff.a <- lapply(eff, function(a) matrix(a[seq(2,length(a), by=2)] - a[seq(1,length(a), by=2)], nrow=1))
    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col, "effects"), eff.a )


    # treat as all females
    fake.f2$pheno$sex <- rep(0, nind(fake.f2))

    pr <- qtl::reviseXdata("f2", "standard", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                           cross.attr=attributes(fake.f2))

    pheno.col <- 1
    eff <- apply(pr, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))

    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col), eff )

    pralt <- qtl::reviseXdata("f2", "full", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                              cross.attr=attributes(fake.f2))
    eff <- apply(pralt, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))
    eff.a <- lapply(eff, function(a) matrix(a[seq(2,length(a), by=2)] - a[seq(1,length(a), by=2)], nrow=1))
    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col, "effects"), eff.a )


    # treat as all forward direction
    fake.f2$pheno$sex <- origsex
    fake.f2$pheno$pgm <- rep(1, nind(fake.f2))

    pr <- qtl::reviseXdata("f2", "standard", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                           cross.attr=attributes(fake.f2))

    pheno.col <- 1
    eff <- apply(pr, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))

    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col), eff )

    eff.a <- lapply(eff, function(a) matrix(a[seq(2,length(a), by=2)] - a[seq(1,length(a), by=2)], nrow=1))
    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col, "effects"), eff.a )


    # treat as all reverse direction
    fake.f2$pheno$pgm <- rep(0, nind(fake.f2))

    pr <- qtl::reviseXdata("f2", "standard", getsex(fake.f2), prob=fake.f2$geno[["X"]]$prob,
                           cross.attr=attributes(fake.f2))

    pheno.col <- 1
    eff <- apply(pr, 2, function(a,b) lm(b ~ -1 + a)$coef, fake.f2$pheno[,1])
    eff <- lapply(as.data.frame(eff), function(a) matrix(a, nrow=1))

    expect_equivalent( estQTLeffects(fake.f2, pheno.col=pheno.col), eff )

    eff.a <- lapply(eff, function(a) matrix(a[seq(2,length(a), by=2)] - a[seq(1,length(a), by=2)], nrow=1))

})

test_that("cbindQTLeffects works", {

    data(grav)
    grav <- qtl::reduce2grid(qtl::calc.genoprob(grav[1:2,], step=5))

    eff <- estQTLeffects(grav, phe=1:5)
    three_eff <- eff
    for(i in seq(along=eff))
        three_eff[[i]] <- cbind(eff[[i]], eff[[i]], eff[[i]])

    expect_equivalent( cbindQTLeffects(eff, eff, eff), three_eff )

})

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qtlcharts documentation built on Oct. 24, 2020, 1:09 a.m.