This vignette will introduce you to how the basic genetic parameters like the allele frequency, the genotype frequency and Hardy-Weinberg Equilibrium results are calculated with mixIndependR.
The dataset imported should be in a format of the genotype data with individuals in rows and markers in columns. Excel, csv and vcf file format are compatible.
#> STR1 SNP1
#> 1 12|12 A|A
#> 2 13|14 T|T
#> 3 13|13 A|T
#> 4 14|15 A|T
#> 5 15|13 T|A
#> 6 13|14 A|T
#> 7 14|13 A|A
#> 8 12|12 T|A
#> 9 14|14 T|T
#> 10 15|15 A|TAlleleFreq calculates the allele frequencies for one dataset.
AlleleFreq(x,sep = "\\|")
#> STR1 SNP1
#> 12 0.2 0.0
#> 13 0.3 0.0
#> 14 0.3 0.0
#> 15 0.2 0.0
#> A 0.0 0.5
#> T 0.0 0.5GenotypeFreq calculates the observed or expected genotype frequency. If expect=FALSE, the observed genotype frequencies from the original dataset will be calculated. If expected=TRUE, the expected genotype probabilities from allele frequency table under Hardy-Weinberg Equilibrium will be exported.
GenotypeFreq(x,sep = "\\|",expect = FALSE) ####or GenotypeFreq(x)
#> STR1 SNP1
#> 12|12 2 0
#> 13|13 1 0
#> 14|14 1 0
#> 15|15 1 0
#> A|A 0 2
#> T|T 0 2
#> 12|13 0 0
#> 12|14 0 0
#> 12|15 0 0
#> 12|A 0 0
#> 12|T 0 0
#> 13|14 2 0
#> 13|15 0 0
#> 13|A 0 0
#> 13|T 0 0
#> 14|15 1 0
#> 14|A 0 0
#> 14|T 0 0
#> 15|A 0 0
#> 15|T 0 0
#> A|T 0 4
#> T|A 0 2
#> T|15 0 0
#> T|14 0 0
#> T|13 0 0
#> T|12 0 0
#> A|15 0 0
#> A|14 0 0
#> A|13 0 0
#> A|12 0 0
#> 15|14 0 0
#> 15|13 1 0
#> 15|12 0 0
#> 14|13 1 0
#> 14|12 0 0
#> 13|12 0 0
GenotypeFreq(x,sep = "\\|",expect = TRUE) ####or GenotypeFreq(x,expect =T)
#> STR1 SNP1
#> 12|12 0.04 0.00
#> 13|13 0.09 0.00
#> 14|14 0.09 0.00
#> 15|15 0.04 0.00
#> A|A 0.00 0.25
#> T|T 0.00 0.25
#> 12|13 0.06 0.00
#> 12|14 0.06 0.00
#> 12|15 0.04 0.00
#> 12|A 0.00 0.00
#> 12|T 0.00 0.00
#> 13|14 0.09 0.00
#> 13|15 0.06 0.00
#> 13|A 0.00 0.00
#> 13|T 0.00 0.00
#> 14|15 0.06 0.00
#> 14|A 0.00 0.00
#> 14|T 0.00 0.00
#> 15|A 0.00 0.00
#> 15|T 0.00 0.00
#> A|T 0.00 0.25
#> T|A 0.00 0.25
#> T|15 0.00 0.00
#> T|14 0.00 0.00
#> T|13 0.00 0.00
#> T|12 0.00 0.00
#> A|15 0.00 0.00
#> A|14 0.00 0.00
#> A|13 0.00 0.00
#> A|12 0.00 0.00
#> 15|14 0.06 0.00
#> 15|13 0.06 0.00
#> 15|12 0.04 0.00
#> 14|13 0.09 0.00
#> 14|12 0.06 0.00
#> 13|12 0.06 0.00Heterozygous test the heterozygosity of each individuals at each locus and output a table with 0 denoting homozygous and 1 heterozygous.
h <-Heterozygous(x,sep = "\\|") ####or Just use Heterozygous(x)
print(h)
#> STR1 SNP1
#> [1,] 0 0
#> [2,] 1 0
#> [3,] 0 1
#> [4,] 1 1
#> [5,] 1 1
#> [6,] 1 1
#> [7,] 1 0
#> [8,] 0 1
#> [9,] 0 0
#> [10,] 0 1RxpHetero calculate Real or Expected Average Heterozygosity at each locus. If HWE=TRUE, this function will calculate the expected heterozygosities under Hardy-Weinberg Equilibrium; If HWE=FALSE, this function will calculate the real average heterozygosities.
AlleleShare calculates the table of number of shared alleles for each pair of individuals at each locus.If replacement=TRUE, the pairs are formed with replicates; if replacement=FALSE, the pairs are formed without replicate.
AS<-AlleleShare(x,sep = "\\|",replacement = FALSE) ###or without "sep="
head(AS)
#> STR1 SNP1
#> 10 2 0 1
#> 1 3 0 1
#> 9 8 0 1
#> 4 6 1 2
#> 7 5 1 1RealProAlleleShare and ExpProAllelShare calculate the average proportions and the expected probabilities of sharing 0,1 and 2 alleles at each locus.
e <-RealProAlleleShare(AS)
e0<-ExpProAlleleShare(p)
head(e)
#> P0 P1 P2
#> STR1 0.6 0.4 0.0
#> SNP1 0.0 0.8 0.2
head(e0)
#> P0 P1 P2
#> STR1 0.317 0.5672 0.1158
#> SNP1 0.125 0.5000 0.3750HWE_Chisq test the Hardy-Weinberg Equilibrium with Pearson’s Chi-square test. B is an integer specifying the number of replicates used in the Monte Carlo test.