summaryRuns: Summary statistics on detected runs

In detectRUNS: Detect Runs of Homozygosity and Runs of Heterozygosity in Diploid Genomes

Description

This function processes the results from slidingRUNS.run and consecutiveRUNS.run and produces a number of interesting descriptives statistics on results.

Usage

summaryRuns(runs, mapFile, genotypeFile, Class = 2, snpInRuns = FALSE)

Arguments

runs	R object (dataframe) with results on detected runs
mapFile	Plink map file (for SNP position)
genotypeFile	Plink ped file (for SNP position)
Class	group of length (in Mbps) by class (default: 0-2, 2-4, 4-8, 8-16, >16)
snpInRuns	TRUE/FALSE (default): should the function snpInsideRuns be called to compute the proportion of times each SNP falls inside a run in the group/population?

Details

summaryRuns calculates: i) the number of runs per chromosome and group/population; ii) the percent distribution of runs per chromosome and group; iii) the number of runs per size-class and group; iv) the percent distribution of runs per size-class and group; v) the mean length of runs per chromosome and group; vi) the mean length of runs per size-class and group; vii) individual inbreeding coefficient estimated from ROH; viii) individual inbreeding coefficient estimated from ROH per chromosome; ix) individual inbreeding coefficient estimated from ROH per size-class

Value

A list of dataframes containing the most relevant descriptives statistics on detected runs. The list conveniently contains 9 dataframes that can be used for further processing and visualization, or can be written out to text files

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')

summaryRuns(runs = runsDF, mapFile = mapFile, genotypeFile = genotypeFile, Class = 2,
snpInRuns = FALSE)

detectRUNS documentation built on Oct. 30, 2019, 11:41 a.m.