Applied Population Genetics Textbook Release

I will be posting portions of all 10 chapters of my upcoming textbook, Applied Population Genetics, as early draft chapters to this website over the spring semester.

This book will be published in both ibook and print-on-demand versions. I prefer the ibook format because I can embed interactive content (movies, JavaScript, etc.) into the text and it will update automatically when I make revisions etc.

The drawback is that ibook is limited to OSX and iOS devices at this time—which is why I will also be making it available as a print-on-demand text (though the interactive content will not obviously be included). The complete text is scheduled to be made available by the end of the academic year and I will be using it as the primary source in my Spring courses of Population Genetics BIOL516 and Landscape Genetics ENVS 692

 

	Chapter 1: Learning R Installation, Package Management, RStudio, Github Data Types Data Containers Basic Programming Graphical Output
	Chapter 2: Hardy-Weinberg Equilibrium Theoretical Foundations & Expectations Testing for Hardy-Weinberg Equilibrium
	Chapter 3: Mutation Causes and Consequences Equilibrium Expectations Estimating Mutation Rates
	Chapter 4: Non-random Mating Genetic Linkage Inbreeding Mixed Mating Systems & Selfing Rates Relatedness
	Chapter 5: Genetic Drift Drift & Structure Allelic & Genotypic Diversity Genetic Effective Population Size Rarefaction
	Chapter 6: Population Subdivision Gene Frequencies & Gene Flow Genetic Distance Genetic Structure
	Chapter 7: Selection The Fundamental Theorem of Natural Selection Neutral Theory Selection on Genotypes Identifying Putative Selection in Outliers & Gradients
	Chapter 8: Spatial Data Spatial Autocorrelation Shapefiles in R Vector Data Raster Data
	Chapter 9: Graph Models Model Free Networks Population Graphs Isolation Models
	Chapter 10: Parent-Offspring Data Pedigree Analyses Parentage Analysis in Populations Pollen Pool Analyses
	Appendices Data sets in gstudio Installing GDAL & RGEOS Spatial Projections Customizing the R Environment About the Author