plot_profile | R Documentation |
Plots profiled logarithm of score-based P-values (LOP) from individual or combined traits.
plot_profile(
data = data,
model = model,
pheno.col = NULL,
sup.int = FALSE,
main = NULL,
legend = "bottom",
ylim = NULL,
grid = FALSE
)
data |
an object of class |
model |
an object of class |
pheno.col |
a numeric vector with the phenotype column numbers to be plotted; if |
sup.int |
if |
main |
a character string with the main title; if |
legend |
legend position (either "bottom", "top", "left" or "right"); if |
ylim |
a numeric value pair supplying the limits of y-axis, e.g. c(0,10); if |
grid |
if |
A ggplot2 with the LOP profiles for each trait.
Guilherme da Silva Pereira, gdasilv@ncsu.edu
Pereira GS, Gemenet DC, Mollinari M, Olukolu BA, Wood JC, Mosquera V, Gruneberg WJ, Khan A, Buell CR, Yencho GC, Zeng ZB (2020) Multiple QTL mapping in autopolyploids: a random-effect model approach with application in a hexaploid sweetpotato full-sib population, Genetics 215 (3): 579-595. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1534/genetics.120.303080")}.
profile_qtl
, remim
# Estimate conditional probabilities using mappoly package
library(mappoly)
library(qtlpoly)
genoprob4x = lapply(maps4x[c(5)], calc_genoprob)
data = read_data(ploidy = 4, geno.prob = genoprob4x, pheno = pheno4x, step = 1)
# Search for QTL
remim.mod = remim(data = data, pheno.col = 1, w.size = 15, sig.fwd = 0.0011493379,
sig.bwd = 0.0002284465, d.sint = 1.5, n.clusters = 1)
# Plot profile
plot_profile(data = data, model = remim.mod, grid = FALSE)
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