search_qtl: QTL forward search
In qtlpoly: Random-Effect Multiple QTL Mapping in Autopolyploids

Description Usage Arguments Value Author(s) References See Also Examples

Searches for QTL and adds them one at a time to a multiple random-effect QTL model based on score statistics.

search_qtl(
  data,
  offset.data = NULL,
  model,
  w.size = 15,
  sig.fwd = 0.2,
  score.null = NULL,
  polygenes = FALSE,
  n.rounds = Inf,
  n.clusters = NULL,
  plot = NULL,
  verbose = TRUE
)

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

`data`	an object of class `qtlpoly.data`.
`offset.data`	a data frame with the same dimensions of `data$pheno` containing offset variables; if `NULL` (default), no offset variables are considered.
`model`	an object of class `qtlpoly.model` from which a forward search will start.
`w.size`	the window size (in cM) to avoid on either side of QTL already in the model when looking for a new QTL.
`sig.fwd`	the desired score-based p-value threshold for forward search, e.g. 0.01 (default).
`score.null`	an object of class `qtlpoly.null` with results of score statistics from resampling.
`polygenes`	if `TRUE` all QTL but the one being tested are treated as a single polygenic effect; if `FALSE` (default) all QTL effect variances have to estimated.
`n.rounds`	number of search rounds; if `Inf` (default) forward search will stop when no more significant positions can be found.
`n.clusters`	number of parallel processes to spawn.
`plot`	a suffix for the file's name containing plots of every QTL search round, e.g. "search" (default); if `NULL`, no file is produced.
`verbose`	if `TRUE` (default), current progress is shown; if `FALSE`, no output is produced.
`x`	an object of class `qtlpoly.search` to be printed.
`pheno.col`	a numeric vector with the phenotype column numbers to be printed; if `NULL`, all phenotypes from `'data'` will be included.
`...`	currently ignored

An object of class qtlpoly.search 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.

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. doi: 10.1534/genetics.120.303080.

Qu L, Guennel T, Marshall SL (2013) Linear score tests for variance components in linear mixed models and applications to genetic association studies. Biometrics 69 (4): 883–92.

Zou F, Fine JP, Hu J, Lin DY (2004) An efficient resampling method for assessing genome-wide statistical significance in mapping quantitative trait loci. Genetics 168 (4): 2307-16. doi: 10.1534/genetics.104.031427

read_data, null_model

  
  # 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)

  # Build null model
  null.mod = null_model(data, pheno.col = 1, n.clusters = 1)

  # Perform forward search
  search.mod = search_qtl(data, model = null.mod, w.size = 15, sig.fwd = 0.01, n.clusters = 1)