detectRUNS (version 0.9.6)

slidingRUNS.run: Main function to detect RUNS (ROHom/ROHet) using sliding windows (a la Plink)

Description

This is one of the main function of detectRUNS and is used to detect runs (of homozygosity or heterozygosity) in the genome (diploid) with the sliding-window method. All parameters to detect runs (e.g. minimum n. of SNP, max n. of missing genotypes, max n. of opposite genotypes etc.) are specified here. Input data are in the ped/map Plink format (https://www.cog-genomics.org/plink/1.9/input#ped)

Usage

slidingRUNS.run(genotypeFile, mapFile, windowSize = 15,
  threshold = 0.05, minSNP = 3, ROHet = FALSE, maxOppWindow = 1,
  maxMissWindow = 1, maxGap = 10^6, minLengthBps = 1000,
  minDensity = 1/1000, maxOppRun = NULL, maxMissRun = NULL)

Arguments

genotypeFile

genotype (.ped) file path

mapFile

map file (.map) file path

windowSize

the size of sliding window (number of SNP loci) (default = 15)

threshold

the threshold of overlapping windows of the same state (homozygous/heterozygous) to call a SNP in a RUN (default = 0.05)

minSNP

minimum n. of SNP in a RUN (default = 3)

ROHet

should we look for ROHet or ROHom? (default = FALSE)

maxOppWindow

max n. of homozygous/heterozygous SNP in the sliding window (default = 1)

maxMissWindow

max. n. of missing SNP in the sliding window (default = 1)

maxGap

max distance between consecutive SNP to be still considered a potential run (default = 10^6 bps)

minLengthBps

minimum length of run in bps (defaults to 1000 bps = 1 kbps)

minDensity

minimum n. of SNP per kbps (defaults to 0.1 = 1 SNP every 10 kbps)

maxOppRun

max n. of opposite genotype SNPs in the run (optional)

maxMissRun

max n. of missing SNPs in the run (optional)

Value

A dataframe with RUNs of Homozygosity or Heterozygosity in the analysed dataset. The returned dataframe contains the following seven columns: "group", "id", "chrom", "nSNP", "from", "to", "lengthBps" (group: population, breed, case/control etc.; id: individual identifier; chrom: chromosome on which the run is located; nSNP: number of SNPs in the run; from: starting position of the run, in bps; to: end position of the run, in bps; lengthBps: size of the run)

Details

This function scans the genome (diploid) for runs using the sliding-window method. This is a wrapper function for many component functions that handle the input data (ped/map files), perform internal conversions, accept parameters specifications, select whether runs of homozygosity (RoHom) or of heterozygosity (RoHet) are looked for.

In the ped file, the groups samples belong to can be specified (first column). This is important if comparisons between human ethnic groups or between animal breeds or plant varieties or biological populations are to be performed. Also, if cases and controls are to be compared, this is the place where this information needs to be specified.

This function returns a data frame with all runs detected in the dataset. This data frame can then be written out to a csv file. The data frame is, in turn, the input for other functions of the detectRUNS package that create plots and produce statistics from the results (see plots and statistics functions in this manual, and/or refer to the detectRUNS vignette).

Examples

# NOT RUN {
# 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 with sliding window approach
# }
# NOT RUN {
# skipping runs calculation
runs <- slidingRUNS.run(genotypeFile, mapFile, windowSize = 15, threshold = 0.1,
minSNP = 15, ROHet = FALSE,  maxOppWindow = 1, maxMissWindow = 1, maxGap=10^6,
minLengthBps = 100000,  minDensity = 1/10000)
# }
# NOT RUN {
# loading pre-calculated data
runsFile <- system.file("extdata", "Kijas2016_Sheep_subset.sliding.csv", package="detectRUNS")
colClasses <- c(rep("character", 3), rep("numeric", 4)  )
runs <- read.csv2(runsFile, header = TRUE, stringsAsFactors = FALSE,
colClasses = colClasses)

# }