tableRuns {detectRUNS}

Function to retrieve most common runs in the population

Description

This function takes in input either the run results or the output from the function snpInsideRuns (proportion of times a SNP is inside a run) in the population/group, and returns a subset of the runs most commonly found in the group/population. The parameter threshold controls the definition of most common (e.g. in at least 50%, 70% etc. of the sampled individuals)

Usage

tableRuns(runs = NULL, SnpInRuns = NULL, genotypeFile, mapFile,
  threshold = 0.5)

Arguments

runs

R object (dataframe) with results on detected runs

SnpInRuns

dataframe with the proportion of times each SNP falls inside a run in the population (output from snpInsideRuns)

genotypeFile

Plink ped file (for SNP position)

mapFile

Plink map file (for SNP position)

threshold

value from 0 to 1 (default 0.7) that controls the desired proportion of individuals carrying that run (e.g. 70%)

Value

A dataframe with the most common runs detected in the sampled individuals (the group/population, start and end position of the run, chromosome and number of SNP included in the run are reported in the output dataframe)

Examples

# getting map and ped paths
genotypeFile <- system.file("extdata", "Kijas2016_Sheep_subset.ped", package = "detectRUNS")
mapFile <- system.file("extdata", "Kijas2016_Sheep_subset.map", package = "detectRUNS")

# calculating runs of Homozygosity
## Not run: 
# skipping runs calculation
runs <- slidingRUNS.run(genotypeFile, mapFile, windowSize = 15, threshold = 0.1,  minSNP = 15,
ROHet = FALSE,  maxOppositeGenotype = 1, maxMiss = 1,  minLengthBps = 100000,  minDensity = 1/10000)

## End(Not run)
# loading pre-calculated data
runsFile <- system.file("extdata", "Kijas2016_Sheep_subset.sliding.csv", package="detectRUNS")
runsDF = readExternalRuns(inputFile = runsFile, program = 'detectRUNS')

tableRuns(runs = runsDF, genotypeFile = genotypeFile, mapFile = mapFile, threshold = 0.5)