qtl2: scan1max – R documentation

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scan1max

Maximum LOD score from genome scan with a single-QTL model

Description

Maximum LOD score from genome scan with a single-QTL model by Haley-Knott regression or a linear mixed model, with possible allowance for covariates.

Usage

scan1max(
  genoprobs,
  pheno,
  kinship = NULL,
  addcovar = NULL,
  Xcovar = NULL,
  intcovar = NULL,
  weights = NULL,
  reml = TRUE,
  model = c("normal", "binary"),
  hsq = NULL,
  by_chr = FALSE,
  cores = 1,
  ...
)

Arguments

`genoprobs`	Genotype probabilities as calculated by `calc_genoprob()`.
`pheno`	A numeric matrix of phenotypes, individuals x phenotypes.
`kinship`	Optional kinship matrix, or a list of kinship matrices (one per chromosome), in order to use the LOCO (leave one chromosome out) method.
`addcovar`	An optional numeric matrix of additive covariates.
`Xcovar`	An optional numeric matrix with additional additive covariates used for null hypothesis when scanning the X chromosome.
`intcovar`	An numeric optional matrix of interactive covariates.
`weights`	An optional numeric vector of positive weights for the individuals. As with the other inputs, it must have `names` for individual identifiers.
`reml`	If `kinship` provided: if `reml=TRUE`, use REML; otherwise maximum likelihood.
`model`	Indicates whether to use a normal model (least squares) or binary model (logistic regression) for the phenotype. If `model="binary"`, the phenotypes must have values in [0, 1].
`hsq`	Considered only if `kinship` is provided, in which case this is taken as the assumed value for the residual heritability. It should be a vector with length corresponding to the number of columns in `pheno`, or (if `kinship` corresponds to a list of LOCO kinship matrices) a matrix with dimension `length(kinship) x ncol(pheno)`.
`by_chr`	If TRUE, save the individual chromosome maxima.
`cores`	Number of CPU cores to use, for parallel calculations. (If `0`, use `parallel::detectCores()`.) Alternatively, this can be links to a set of cluster sockets, as produced by `parallel::makeCluster()`.
`...`	Additional control parameters; see Details.

Details

Equivalent to running scan1() and then saving the column maxima, with some savings in memory usage.

Value

Either a vector of genome-wide maximum LOD scores, or if by_chr is TRUE, a matrix with the chromosome-specific maxima, with the rows being the chromosomes and the columns being the phenotypes.

Examples

# read data
iron <- read_cross2(system.file("extdata", "iron.zip", package="qtl2"))


# insert pseudomarkers into map
map <- insert_pseudomarkers(iron$gmap, step=1)

# calculate genotype probabilities
probs <- calc_genoprob(iron, map, error_prob=0.002)

# grab phenotypes and covariates; ensure that covariates have names attribute
pheno <- iron$pheno
covar <- match(iron$covar$sex, c("f", "m")) # make numeric
names(covar) <- rownames(iron$covar)
Xcovar <- get_x_covar(iron)

# perform genome scan
out <- scan1max(probs, pheno, addcovar=covar, Xcovar=Xcovar)

qtl2

Quantitative Trait Locus Mapping in Experimental Crosses

v0.24

GPL-3

Authors

Karl W Broman [aut, cre] (<https://orcid.org/0000-0002-4914-6671>), R Core Team [ctb]

Initial release

2020-12-16