mungeData: mungeData In HWxtest: Exact Tests for Hardy-Weinberg Proportions

Description

Utility functions for handling genotype counts and arranging data

remove missing alleles

converts matrix to vector

Clears upper-right of matrix

Usage

 1 2 3 4 5 6 7 8 9 10 11 12 13 fillUpper(gmat) alleleCounts(gmat) vec.to.matrix(gvec, alleleNames = "") remove.missing.alleles(gmat) matrix.to.vec(gmat) clearUpper(gmat) df.to.matrices(df, sep = "/")

Arguments

 gmat a matrix of non-negative integers representing genotype counts. In a matrix of genotype counts, a[i,j] and a[j,i] both represent the same heterozygote. Only the lower-left half of gmat is used. Numbers along the diagonal represent counts of the homozygotes. gvec vector containing k(k+1)/2 genotype counts. All non-negative integers. Genotype counts should be in the order: a11, a21, a22, a31, a32, ..., akk alleleNames an optional list of names for the alleles. The length should be k df a dataframe containing individual genotypes. Each row represents an individual. The first column, named “pop” names the population. Each other column is named for a particular locus. The genotypes are as “123/124” sep For a dataframe, this is the separator character. typically “/”

Details

Interconvert between different formats for genotype counts.

Let k be the number of alleles:

• clearUpper fills the upper-right half of the k x k matrix with NA

• fillUpper makes the k x k matrix symmetrical by filling the upper-right half with numbers from the lower half.

• vec.to.matrix converts genotype counts in vector form and returns a matrix. The vector must have k(k+1)/2 non-negative integers.

• matrix.to.vec converts a k x k matrix of genotype counts to a vector of length k(k+1)/2

• alleleCounts returns a vector of length k containing the numbers of each allele. The sum of this vector will be twice the number of diploids in the sample.

• remove.missing.alleles returns a matrix with no 0's for allele counts

• df.to.matrices converts a data frame to a list of genotype count matrices. The data frame should be of the kind produced in the package adegenet with genind2df

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Examples

 1 2 3 gvec <- c(0,3,1,5,18,1,3,7,5,2) gmat <- vec.to.matrix(gvec, alleleNames=letters[1:4]) alleleCounts(gmat)

HWxtest documentation built on May 31, 2019, 9:04 a.m.