Permutation Testing for Isotonic Inference on Association Studies in Genetics : SpringerBriefs in Statistics - Luigi Salmaso

eTEXT

Permutation Testing for Isotonic Inference on Association Studies in Genetics

By: Luigi Salmaso, Rosa Arboretti, Livio Corain, Dario Mazzaro

eText | 9 July 2011

At a Glance

eText


$84.99

or 4 interest-free payments of $21.25 with

 or 

Instant online reading in your Booktopia eTextbook Library *

Read online on
Desktop
Tablet
Mobile

Not downloadable to your eReader or an app

Why choose an eTextbook?

Instant Access *

Purchase and read your book immediately

Read Aloud

Listen and follow along as Bookshelf reads to you

Study Tools

Built-in study tools like highlights and more

* eTextbooks are not downloadable to your eReader or an app and can be accessed via web browsers only. You must be connected to the internet and have no technical issues with your device or browser that could prevent the eTextbook from operating.

The purpose of this book is to illustrate a new statistical approach to test allelic association and genotype-specific effects in the genetic study of diseases. There are some parametric and non-parametric methods available for this purpose. We deal with population-based association studies, but comparisons with other methods will also be drawn, analysing the advantages and disadvantages of each one, particularly with regard to power properties with small sample sizes. In this framework we will work out some nonparametric statistical permutation tests and likelihood-based tests to perform case-control analyses to study allelic association between marker, disease-gene and environmental factors. Permutation tests, in particular, will be extended to multivariate and more complex studies, where we deal with several genes and several alleles together. Furthermore, we show simulations under different assumptions on the genetic model and analyse real data sets by simply studying one locus with the permutation test.

Read online on
Desktop
Tablet
Mobile

More in Epidemiology & Medical Statistics