---
title: "Basic Genetics"
description: Learn how to use mixIndependR to obtain basic genetic parameters
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Basic Genetics}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---
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`.


```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```


```{r setup}
```

## Package Installation
```{r load packages, include=FALSE}
library(mixIndependR)
```

## Data Import

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.

`mixexample` is an attached data in this package, which is the genotypes of 2504 individuals on 100 unlined variants including 6 STRs and 94 SNPs.
```{r import}
x <- mixexample
```
## Basic Genetic Parameters

`AlleleFreq` calculates the allele frequencies for one dataset.

```{r allele freq, echo=TRUE}
p <- AlleleFreq(x,sep = "\\|")
```
`GenotypeFreq` 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.

```{r genotype freq, echo=TRUE}
G <- GenotypeFreq(x,sep = "\\|",expect = FALSE) 
G0 <- GenotypeFreq(x,sep = "\\|",expect = TRUE) 
```
`Heterozygous` test the heterozygosity of each individuals at each locus and output a table with `0` denoting homozygous and `1` heterozygous.

```{r Heterozygosity, echo=TRUE}
h <-Heterozygous(x,sep = "\\|") ####or Just use Heterozygous(x)
```
`RxpHetero` 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.

```{r Hetero Expect, echo=TRUE}
H <- RxpHetero(h,p,HWE=TRUE)
```
`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 replacement; if `replacement=FALSE`, the pairs are formed without replacement. When the sample size is large, `replacement=F` is much faster.

```{r AS}
AS<-AlleleShare(x,sep = "\\|",replacement = FALSE) 
```
`RealProAlleleShare` and `ExpProAllelShare` calculate the average proportions and the expected probabilities of sharing 0,1 and 2 alleles at each locus.


```{r Allele Share Expect, message=FALSE, warning=FALSE}
e <-RealProAlleleShare(AS)
e0<-ExpProAlleleShare(p)
```

`HWE_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.

```{r HWE}

HWE_pvalue <-HWE.Chisq(G,G0,rescale.p = T,simulate.p.value = T,B=2000)
```