This function performs marker regression to associate individual markers with traits (or eigentraits). If n_perm is greater than 0, permutations are run to determine effect size thresholds for the alpha values provided. The default alpha values are 0.05 and 0.01. Covariates are specified in the cape parameter file.
singlescan(
data_obj,
geno_obj,
kin_obj = NULL,
n_perm = 0,
alpha = c(0.01, 0.05),
model_family = "gaussian",
run_parallel = FALSE,
n_cores = 4,
verbose = FALSE,
overwrite_alert = TRUE
)Returns a list of the singlescan results. The list is of length seven, and has the following elements: alpha: The alpha values set in the argument alpha alpha_thresh: The calculated effect size thresholds at each alpha if permutations are run. ref_allele: The allele used as the reference allele singlescan_effects: The effect sizes (beta coefficients) from the single-locus linear models singlescan_t_stats: The t statistics from the single-locus linear models locus.p_vals: Marker-level p values locus_score_scores: Marker-level test statistics.
a Cape object
a genotype object.
a kinship object. If NULL, the kinship correction is not performed.
integer number of permutations. Permutation results are only
used in plot_singlescan. They are not used for any other piece
of the Cape analysis and may be safely omitted. The default number of permutations
is 0.
significance level if permutations are being run. If permutations are run effect size thresholds for each alpha level are cacluated using the extreme value distribution.
A vector indicating the model family of the phenotypes. This can be either "gaussian" or "binomial." If length 1, all phenotypes will be assigned to the same family. Phenotypes can be assigned different model families by providing a vector of the same length as the number of phenotypes, indicating how each phenotype should be modeled.
Whether to run on parallel CPUs
The number of CPUs to use if run_parallel is TRUE
Whether to print progress to the screen
Used
model_family indicates the model family of the phenotypes This can be either "gaussian" or "binomial". If this argument is length 1, all phenotypes will be assigned to the same family. Phenotypes can be assigned different model families by providing a vector of the same length as the number of phenotypes, indicating how each phenotype should be modeled.
plot_singlescan