In pujana-lab/systematicQTL: Pipeline to run sistematically QTL analysis

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(systematicQTL)

Data loading

We generate some sample data, genotypes and phenotypes, to show the functions of the package then, as the first step of the pipeline we generate the QTL cross2 object class with the function build_cross2_dataset.

geno_filename = '../tests/testthat/random.genotypes.csvs'
pheno_filename  = '../tests/testthat/random.pheno.csv'

chosen_alleles      = c('A','B')
chosen_covars       = c('pheno_var1', 'pheno_var2', 'pheno_var3')
chosen_phenotypes   = c('signature1', 'signature2', 'signature3')

cross2 = systematicQTL::build_cross2_dataset(
  geno_filename = geno_filename,
  pheno_filename = pheno_filename,
  covar_column_names = chosen_covars,
  pheno_column_names = chosen_phenotypes,
  alleles = chosen_alleles
)

qtl_wrapper = systematicQTL::QtlWrapper(qtl = cross2)

Define LOD thresholds

Next step is to set the minimal threshold for all signatures (0.5) and define the empirical significance value of the LOD

qtl_wrapper = systematicQTL::set_significance_lod(qtl_wrapper,0.5)

qtl_wrapper = systematicQTL::set_empirical_significance_lod(qtl_wrapper, 100, 0.05, 1)

Compute peaks and describe them

We then find the peaks in a set of LOD curves with find_peaks and draw a plot for each phenotype peaks with build_genescan_plot.

qtl_wrapper = systematicQTL::find_peaks(qtl_wrapper)

for(phenotype in qtl_wrapper@phenotypes){
  systematicQTL::build_genescan_plot(qtl_wrapper, phenotype, sprintf('Pheno: %s', phenotype))
}

Extract significant lod scores for markers

Finally we retrieve the LOD scores from the QTL object.

lods = systematicQTL::lod(qtl_wrapper)

for( i in 1:nrow(lods)){
  this_lod = lods[i,]
  systematicQTL::build_pdx_plot(
    qtl_wrapper, chr = this_lod$chr, cm = this_lod$cm, 'signature1', 
    sprintf('%s-signature1', this_lod$snp),
    sprintf('LOD score: %.3f, (tresh. %.3f)', this_lod$signature1, this_lod$signature1.threshold)
  )
}

print(lods)