Basics of Modern Statistical Genetics

Inbunden, Engelska, 2016

2 389 kr

Slutsåld

Over the past 40 years we have seen significant advances in the use of genetics to study subjects from evolution and ecology to medicine and human health. Early protein and restriction analysis studies have given way to high-throughput sequencing and genome-wide studies. With these advances has come the need for increasingly complex statistical analyses. This has come in the form of multifaceted algorithms such as eigenanalysis and Bayesian analysis. Bayesian analysis has become one of the most widely used techniques in modern statistical genetics as the use of Markov chain Monte Carlo (MCMC) methods have made it relatively quick and simple to incorporate prior information into the model. Gene mapping studies have also become increasingly widespread as candidate genes are being found for a number of phenotypes, conditions, and diseases. In this book we look at a number of novel techniques used to study populations, phenotypes, and gene expression in organisms as diverse as humans and plants. We end with three case studies applying statistical genetics to identify genes associated with human diseases.

Produktinformation

Utgivningsdatum2016-11-30
Mått152 x 229 x undefined mm
Vikt1 100 g
FormatInbunden
SpråkEngelska
Antal sidor260
FörlagDelve Publishing
ISBN9781680957426

Tillhör följande kategorier

Medicinsk genetik inom Medicin
Biovetenskap inom Naturvetenskap och teknik

Linda Lait obtained her MSc from the University of Lethbridge in 2011 and will be completing her PhD at Memorial University of Newfoundland in 2016. Her interests include the evolutionary history of species, particularly those of conservation concern, which she studies with molecular markers. Increasingly complex questions can be answered with the improved technologies that are emerging. She is currently finishing up her PhD in molecular genetics, and will be starting as a Postdoctoral Fellow studying phylogeography and molecular evolution in insects.