feim {qtlpoly}

Fixed-effect interval mapping (FEIM)

Description

Performs interval mapping using the single-QTL, fixed-effect model proposed by Hackett et al. (2001).

Usage

feim(
  data = data,
  pheno.col = NULL,
  w.size = 15,
  sig.lod = 7,
  d.sint = 1.5,
  plot = NULL,
  verbose = TRUE
)

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

Arguments

data

an object of class qtlpoly.data.

pheno.col

a numeric vector with the phenotype columns to be analyzed; if NULL (default), all phenotypes from 'data' will be included.

w.size

a number representing the window size (in centiMorgans) to be avoided on either side of QTL already in the model when looking for a new QTL, e.g. 15 (default).

sig.lod

the vector of desired significance LOD thresholds (usually permutation-based) for declaring a QTL for each trait, e.g. 5 (default); if a single value is provided, the same LOD threshold will be applied to all traits.

d.sint

a d value to subtract from logarithm of the odds (LOD-d) for support interval calculation, e.g. d=1.5 (default) represents approximate 95% support interval.

plot

a suffix for the file's name containing plots of every algorithm step, e.g. "remim" (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.feim to be printed.

sint

whether "upper" or "lower" support intervals should be printed; if NULL (default), QTL peak information will be printed.

...

currently ignored

Value

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

pheno.col

a phenotype column number.

LRT

a vector containing LRT values.

LOD

a vector containing LOD scores.

AdjR2

a vector containing adjusted R^2.

qtls

a data frame with information from the mapped QTL.

lower

a data frame with information from the lower support interval of mapped QTL.

upper

a data frame with information from the upper support interval of 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.

Hackett CA, Bradshaw JE, McNicol JW (2001) Interval mapping of quantitative trait loci in autotetraploid species, Genetics 159: 1819-1832.

See Also

permutations

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 = 5)

  # Perform remim
  feim.mod = feim(data = data, sig.lod = 7)