htspop

Overview

htspop is a R package designed for analysis and computation of population genetic statistics using high-dimensional biallelic data. It includes the following statistics:

• Reich's f2, f3, and f4 statistics, similar to treemix implementation.
• Patterson's D statistics (also known ABBA/BABA test).
• jackknife mean estimator.
• Reich, Weir & Cockerham, Hudson, and Wright Fst and their bootstrap estimation.
• Nei's standard and Da genetic distance and a bootstrap estimator.

Instalation

You may install the development version, using devtools

# devtools instalation
devtools::install_github("andremrsantos/htspop")

Usage

## Simulate genotype matrix
geno <- matrix(sample(0:2, 100, replace = TRUE), ncol = 10)
## Convert into Allele Count structure
ac <- ac_matrix_from_genotype(geno) 
## Run F Statistics
jackknife(f4_stat(ac, c(1, 2, 3, 4)))
jackknife(f3_stat(ac, c(1, 2, 3)))
## Run D Statistics
jackknife(d_stat(ac, c(1, 2, 3, 4)))
## Compute Weir & Cockerham Fst and Nei Standard Genetic Distance
fst(ac, "wc")
nei(ac)

Citation

If you use htspop, please specify the version and cite:

Ribeiro-dos-Santos, AM, de Souza, SJ (2018) Htspop: high-troughput sequencing population genetic functions.

Contact

Create an issue to report bugs, propose new functions or ask for help. Please take in consideration this project is under development.

André M. Ribeiro-dos-Santos, andremrsantos@gmail.com