snpStats (version 1.22.0)

row.summary: Summarize rows or columns of a snp matrix

Description

These function calculates summary statistics of each row or column of call rates and heterozygosity for each row of a an object of class "SnpMatrix" or "XSnpMatrix"

Usage

row.summary(object) col.summary(object, rules = NULL, uncertain = TRUE)

Arguments

object
genotype data as a SnpMatrix-class or XSnpMatrix-class object
rules
An object of class "ImputationRules". If supplied, the rules coded in this object are used, together with the snp genotype data in object, to generate imputed SNPs. The column summary of these imputed data are then returned
uncertain
If TRUE uncertain genotypes are used in calculation of allele and genotype frequencies (by scoring as posterior expectations). Otherwise, and for Hardy-Weinberg tests, they are ignored

Value

row.summary
returns a data frame with rows corresponding to rows of the input object and with columns/elements:
  • Call.rate: Proportion of SNPs called
  • Certain.calls: Proportion of called SNPs with certain calls
  • Heterozygosity: Proportion of called SNPs which are heterozygous
Uncertain calls are ignored for calculating the heterozygosity.
col.summary
returns a data frame with rows corresponding to columns of the input object and with columns/elements:
  • Calls: The number of valid calls
  • Call.rate: The proportion of genotypes called
  • Certain.calls: Proportion of called SNPs with certain calls
  • RAF: The "risk" allele (allele B) frequency
  • MAF: The minor allele frequency
  • P.AA: The frequency of homozygous genotype 1 (A/A)
  • P.AB: The frequency of heterozygous genotype 2 (A/B)
  • P.BB: The frequency of homozygous genotype 3 (B/B)
  • z.HWE: A z-test for Hardy-Weinberg equilibrium
For objects of class "XSnpMatrix", the following additional columns are returned:
  • P.AY: The frequency of allele A in males
  • P.BY: The frequency of allele B in males
  • Calls.female: The number of valid calls in females (only these calls are used in the z-test for HWE)

Examples

Run this code
data(testdata)
rs <- row.summary(Autosomes)
summary(rs)
cs <- col.summary(Autosomes)
summary(cs)
cs <- col.summary(Xchromosome)
summary(cs)

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