Inbreeding: Sample inbreeding check with SeqSQC object input file.

In Liubuntu/SeqSQC: A bioconductor package for sample quality check with next generation sequencing data

Sample inbreeding check with SeqSQC object input file.

Description

Function to calculate population-specific inbreeding coefficients, and to predict inbreeding outliers that are five standard deviation beyond the mean.

Usage

Inbreeding(
  seqfile,
  remove.samples = NULL,
  LDprune = TRUE,
  missing.rate = 0.1,
  ss.cutoff = 300,
  maf = 0.01,
  hwe = 1e-06,
  ...
)

Arguments

seqfile	SeqSQC object, which includes the merged gds file for study cohort and benchmark.
remove.samples	a vector of sample names for removal from inbreeding coefficient calculation. Could be problematic samples identified from previous QC steps, or user-defined samples.
LDprune	whether to use LD-pruned snp set. The default is TRUE.
missing.rate	to use the SNPs with "<= missing.rate" only; if NaN, no threshold. By default, we use missing.rate = 0.1 to filter out variants with missing rate greater than 10%.
ss.cutoff	the minimum sample size (300 by default) to apply the MAF filter. This sample size is the sum of study samples and the benchmark samples of the same population as the study cohort.
maf	to use the SNPs with ">= maf" if sample size defined in above argument is greater than ss.cutoff; otherwise NaN is used by default for no MAF threshold.
hwe	to use the SNPs with Hardy-Weinberg equilibrium p >= hwe if sample size defined in above argument is greater than ss.cutoff; otherwise no hwe threshold. The default is 1e-6.
...	Arguments to be passed to other methods.

Details

Using LD-pruned variants (by default), we calculate the inbreeding coefficients for each sample in the study cohort and for benchmark samples of the same population as the study cohort. Samples with inbreeding coefficients that are five standard deviations beyond the mean are considered problematic and are shown as "Yes" in the column of outlier.5sd. Benchmark samples in this column are set to be “NA”.

Value

a data frame with sample name, inbreeding coefficient, and an indicator of whether the inbreeding coefficient is five standard deviation beyond the mean.

Author(s)

Qian Liu [e-mail]

Examples

load(system.file("extdata", "example.seqfile.Rdata", package="SeqSQC"))
gfile <- system.file("extdata", "example.gds", package="SeqSQC")
seqfile <- SeqSQC(gdsfile = gfile, QCresult = QCresult(seqfile))
seqfile <- Inbreeding(seqfile, remove.samples=NULL, LDprune=TRUE, missing.rate=0.1)
res.inb <- QCresult(seqfile)$Inbreeding
tail(res.inb)

Liubuntu/SeqSQC documentation built on April 12, 2024, 6:39 p.m.