All functions

add_pmap()

Add physical map contents to tibble

boot_pvl()

Perform bootstrap sampling and calculate test statistic for each bootstrap sample

calc_Bhat()

Calculate estimated allele effects, B matrix

calc_Sigma()

Calculate the phenotypes covariance matrix Sigma

calc_covs()

Calculate Vg and Ve from d-variate phenotype and kinship

calc_invsqrt_mat()

Calculate matrix inverse square root for a covariance matrix

calc_lrt_tib()

Calculate a likelihood ratio test statistic from the output of scan_pvl()

calc_profile_lods()

Calculate profile lods for all traits

calc_sqrt_mat()

Calculate matrix square root for a covariance matrix

check_identical()

Check whether a vector, x, has all its entries equal to its first entry

check_missingness()

Check for missingness in phenotypes or covariates

convert_to_scan1_output()

Convert scan_multi_oneqtl output of qtl2::scan1 output

find_pleio_peak_tib()

Find the marker index corresponding to the peak of the pleiotropy trace in a tibble where the last column contains log likelihood values and the first d columns contain marker ids

fit1_pvl()

Fit a model for a specified d-tuple of markers

get_effects()

Extract founder allele effects at a single marker from output of qtl2::scan1coef

make_id2keep()

Identify shared subject ids among all inputs: covariates, allele probabilities array, kinship, and phenotypes

plot_pvl()

Plot tidied results of a pvl scan

prep_X_list()

Create a list of component X matrices for input to stagger_mats, to ultimately create design matrix

prep_mytab()

Prepare mytab object for use within scan_pvl R code

process_inputs()

Process inputs to scan functions

qtl2pleio

qtl2pleio.

rcpp_calc_Bhat()

Estimate allele effects matrix, B hat, with Rcpp functions

rcpp_calc_Bhat2()

Estimate allele effects matrix, B hat, with Rcpp functions

rcpp_log_dmvnorm2()

Calculate log likelihood for a multivariate normal

scan_multi_onechr()

Perform multivariate, one-QTL model fitting for markers on one chromosome

scan_multi_oneqtl()

Perform multivariate, one-QTL model fitting for markers on all chromosomes

scan_multi_oneqtl_perm()

Permute the phenotypes matrix and then scan the genome. Record the genomewide greatest LOD score for each permuted data set.

scan_pvl()

Perform model fitting for all ordered pairs of markers in a genomic region of interest

sim1()

Simulate a single multivariate data set consisting of n subjects and d phenotypes for each

subset_input()

Subset an input object - allele probabilities array or phenotypes matrix or covariates matrix. Kinship has its own subset function

subset_kinship()

Subset a kinship matrix to include only those subjects present in all inputs