modify_qtl {qtlpoly}

Modify QTL model

Description

Adds or removes QTL manually from a given model.

Usage

modify_qtl(
  model,
  pheno.col = NULL,
  add.qtl = NULL,
  drop.qtl = NULL,
  verbose = TRUE
)

## S3 method for class 'qtlpoly.modify'
print(x, pheno.col = NULL, ...)

Arguments

model

an object of class qtlpoly.model containing the QTL to be modified.

pheno.col

a phenotype column number whose model will be modified or printed.

add.qtl

a marker position number to be added.

drop.qtl

a marker position number to be removed.

verbose

if TRUE (default), current progress is shown; if FALSE, no output is produced.

x

an object of class qtlpoly.modify to be printed.

...

currently ignored

Value

An object of class qtlpoly.modify which contains a list of results for each trait with the following components:

pheno.col

a phenotype column number.

stat

a vector containing values from score statistics.

pval

a vector containing p-values from score statistics.

qtls

a data frame with information from the mapped QTL.

Author(s)

Guilherme da Silva Pereira, [e-mail]

References

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. doi:10.1534/genetics.120.303080.

See Also

read_data, remim

Examples

  
  # 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)

  # Modify model
  modified.mod = modify_qtl(model = remim.mod, pheno.col = 1, drop.qtl = 18)