View source: R/summary_scan1perm.R
summary_scan1perm | R Documentation |
Summarize permutation test results from scan1perm()
, as significance thresholds.
summary_scan1perm(object, alpha = 0.05)
## S3 method for class 'scan1perm'
summary(object, alpha = 0.05, ...)
object |
An object of class |
alpha |
Vector of significance levels |
... |
Ignored |
In the case of X-chromosome-specific permutations (when
scan1perm()
was run with perm_Xsp=TRUE
, we
follow the approach of Broman et al. (2006) to get separate
thresholds for the autosomes and X chromosome, using
Let L_A
and L_X
be total the genetic lengths of the
autosomes and X chromosome, respectively, and let L_T = L_A +
L_X
Then in place of \alpha
, we use
\alpha_A =
1 - (1-\alpha)^{L_A/L_T}
as the significance level for the autosomes and
\alpha_X = 1 -
(1-\alpha)^{L_X/L_T}
as the significance level for the X chromosome.
An object of class summary.scan1perm
. If
scan1perm()
was run with perm_Xsp=FALSE
, this is
a single matrix of significance thresholds, with rows being
signicance levels and columns being the columns in the input. If
scan1perm()
was run with perm_Xsp=TRUE
, this is
a list of two matrices, with the significance thresholds for the
autosomes and X chromosome, respectively.
The result has an attribute "n_perm"
that has the numbers of
permutation replicates (either a matrix or a list of two matrices).
Broman KW, Sen Ś, Owens SE, Manichaikul A, Southard-Smith EM, Churchill GA (2006) The X chromosome in quantitative trait locus mapping. Genetics 174:2151-2158
# 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)
# permutations with genome scan (just 3 replicates, for illustration)
operm <- scan1perm(probs, pheno, addcovar=covar, Xcovar=Xcovar,
n_perm=3)
summary(operm, alpha=c(0.20, 0.05))
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